Wireless Voice Controlled (Natural Language Processing)

Wireless Voice Controlled (Natural Language Processing)
WIRELESS VOICE CONTROLLED (NATURAL LANGUAGE PROCESSING) HOME AUTOMATION SYSTEM
ABSTRACT
Automation is an upcoming technology of 21st century. The important reason automation gaining its popularity is reducing human effort, interaction
and to reduce human errors. With the improvement in latest technologies, smartphones have become an essential gadget to all. For 2016, the number of
Smartphone users is forecast to reach 2.1 billion. Another upcoming technology is the natural language processing which uses human voice for
commands. Combining all of these technologies, the project presents a wireless voice controlled home automation system. Such a system will be
helpful for senior citizens and physically disabled persons who are in need ... Show more content on Helpwriting.net ...
2.SYSTEM DESIGN
2.1.System Components
2.2.Figure 1: Architecture Diagram of the System
The Voice–operated Android and Arduino Home automation system uses an Android based Bluetooth enabled phone for its application and the
Arduino Uno as the microcontroller. The key components of this system are:
Android Smartphone
Arduino UNO board
ESP8266 Wi–Fi module
Relays
Light bulbs / LED's
2.2.1.Android Based Phone
Android is a mobile operating system (OS) based on the Linux kernel and currently developed by Google. With a user interface based on direct
manipulation, the OS uses touch inputs that loosely correspond to real–world actions, like swiping, tapping, pinching, and reverse pinching to
manipulate on–screen objects, and a virtual keyboard. We have used the Android platform because of its huge market globally and it's easy to use user
interface. Applications on the Android phones extend the functionality of devices and are written primarily in the Java programming language using
the Android software development kit (SDK). The voice recognizer which is an in built feature of Android phones is used to build an application
which the user can operate to automate the appliances in his house.
2.1.2 Arduino

Arduino is an open source prototyping platform easy to use on software as well as hardware. The board can programmed to switch on/off electronic
appliances using ARDUINO (IDE).
2.1.3 Wi–Fi Module
This allows the Arduino board to connect to android
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Multi Label Semantic Relation Classification
Multi–label Semantic Relation Classification
Between Pair of Nominals
Kartik Dhiwar,
PG Scholar, Department of Computer Science and Engineering, SSGI, SSTC, Bhilai (CG), India kartikdhiwar21@gmail.com Abhishek Kumar
Dewangan
Professor, Department of Computer Science and Engineering, SSGI, SSTC, Bhilai (CG), India abhishek.dew2006@gmail.com Abstract: Relation
classification is a keynote in the field of Natu–ral Language Processing (NLP) to mine information from text facing problems of over–reliance on the
standard of handcrafted features. Features annotated by specialists and lin–guistic data derived from linguistic analysis modules is expen–sive and ends
up with the difficulty of error propagation. Rela–tion extraction plays a crucial role in extracting struc–tured data from unstructured sources like raw
text. One might want to seek out interactions between medicines to create medical information or extract relationships among people to create a simply
searchable knowledgebase. We propose a deep Convolutional Neural Network model for the multi–label text relation classification task without hand
crafted features. This model outperforms the best existing model as per our knowledge without depending much on manually engineered features with
the small updates in the loss function applied.
Index Terms– Relation Classification, Features, Label, Convolutional Neural Network, Information Extraction.
.
1.INTRODUCTION
Natural Language Processing tasks are now applicable to

Performance For Web Documents Mining Using Nlp And Latent...
A
THESIS
On
Performance for Web document mining using NLP and Latent Semantic Indexing with Singular Value Decomposition
ABSTRACT
In this thesis we propose a description Web based document file can be say that Latent Semantic Indexing is a application for information sentence and
word based retrieval that promises to offer better performance by incapacitating approximately limits that waves outdated term identical methods. These
word matching techniques have constantly relied on matching query terms with document terms to retrieve the documents having terms matching the
query terms. However, by use of these traditional retrieval techniques, user's no need for adequately helped. While users want to search through
information based on conceptual content, natural languages have limited the expression for such area of study. By Using Cholesky decomposition
finds the lower triangular matrix that satisfies . For instance, with two random variables the decomposition is done as worked. Although, a determinant
of the correlation matrix of the main variables does not have to be positive and in that case other transformation methods can be applied. NLP (natural
language processing)is used for stemming, stop word and they show problem for polynomial series for the sentence . Due to these natural language
problems, individual words contained in user's queries, may not clearly specify the intended user's concept that find the result in retrieval of some
unrelated

Automatic Summarization Of News Articles Using Textrank
AUTOMATIC SUMMARIZATION OF NEWS ARTICLES USING TEXTRANK
ABSTRACT:
With an increase in the amount of information consumed every day, time is a prime resource. Keeping up with current events is an activity that is
essential for everyone, but saving time is also important. Our paper is mainly focused on the implementation of Natural Language Processing
techniques and algorithms to summarize news articles from public sources such that they can be consumed in a short amount of time, keeping the user
updated of global as well as local events. We first provide an Introduction by stating problems faced, and an overview of NLP and Automatic
Summarization. We then survey different types of Summarization, and detail a solution using the TextRank algorithm, along with our proposed
implementation.
1. INTRODUCTION:
In today's world time is limited but the information available online is in excess. With the advent of personal mobile computing devices, we are being
presented with a barrage of information every minute. This makes it increasingly important to consume as much information as possible in the least
amount of time, while eliminating irrelevant and redundant data. News is another domain which falls prey to this information overload. With the
emergence of lightning–fast news delivery through social media services such as Twitter, Facebook well as various News Sources, It is a dire need of
the day to save time and grasp just enough information that is required about current

How Internet Slangs Affect language?
We decided to conduct a questionnaire for the use of Internet slangs within the age group ranging from 14 to 30, which most of the people within this
age group is contacting with Internet slangs most frequently. For the questionnaire, we interviewed one hundred people and student in City University
of Hong Kong, and half of interviewees are boys while the others are girls. The template of questionnaire is attached as appendix for reference, and
the result and data collected are shown as below. It is expected that the use of Internet slangs among this age group is widely distributed, and most of
them have used Internet slangs. More precisely, it is shown that female has a higher rate of using Internet slangs than male. It is predicted that girls
would like to use more medium to express their feeling, such as LOL, OMG. It may also due to the demand of shortening the communication time or
error on texting. The acknowledgement of some popular Internet slangs is expected to be recognized widely by them. However, some of those less
frequently used or new Internet slangs may not be understood by some of them. It is expected that the understanding of Internet slangs will be
increased with the development of Internet slangs or the popularity of that term. The result proved that texting is the most frequently used medium for
Internet slangs, it is possible that the use of Internet slangs can facilitate the communication. The results also revealed that they seldom use

Academic Roles And Academic Leadership
Introduction Many academic advisers sit on the margins within the academy due to the professionalization, casualization and discursive complexity of
the academic language and learning workforce (Percy, 2011; Stevenson & Kokkinn, 2007). Moreover, academic advisers are also responsible in
providing effective feedback and support to all students internal and external to the university; some considering feedback being the most important
aspect of the assessment practices (Price, Handley, Millar, & O 'Donovan, 2010). Nevertheless, advisers in drop–in centres across Australia are time
restrained and are limited to the amount of editing and proofreading they are willing, or able to do. Moreover, EFL/ESL students are in dire need of
greater grammatical, editing and proofreading support and service from the university. Above and beyond the student and the adviser, tutors further
exacerbate the situation by providing feedback to the student as a product rather than a long term process (Price, Handley, & Millar, 2011). One of
the strategies to deal with this issue is to reconceptualise the objective and role of feedback from advisers and tutors, and to develop more holistic
self–directed and university driven feedback approaches (Merry, Price, Carless, & Taras, 2013, p. 41). One method to reconceptualise this is the
implementation of either a learning centre specific, or institutionally wide grammar checking program. With the developments of artificial intelligence,
algorithmic

Side Effects Of Cyber Bullying
Social media is a phrase that we throw around a lot these days, often to describe what we post on sites and apps like Facebook, Twitter, Instagram,
Snapchat and others. The "social" part: refers to interacting with other people by sharing information with them and receiving information from them.
The "media" part: refers to an instrument of communication, like the internet (while TV, radio, and newspapers are examples of more traditional forms
of media). Social media are web–based communication tools that enable people to interact with each other by both sharing and consuming
information. However, social media may have some side effects such as cyberbullying, which may have negative impacts on the life of people,
especially children and teenagers. Cyberbullying can be defined as aggressive, intentional actions performed by an individual or a group of people via
digital communication methods such as sending messages and posting comments against a victim. Different from traditional bullying that usually
occurs at school during face–to–face communication, cyberbullying on social media can take place anywhere at any time. For bullies, they are free to
hurt their peers' feelings because they do not need to face someone and can hide behind the Internet. For victims, they are easily exposed to harassment
since all of us, especially youth, are constantly connected to Internet or social media. As reported cyberbullying victimization rate ranges from 10% to
40%. In the United States,

Symbolism in Bernard Malamud's The Natural Essay
Symbolism in Bernard Malamud's The Natural
The role of symbolism in Bernard Malamud's The Natural is important in helping the reader understand the theme and meaning of the novel as well as
the time period in which it took place. MalamudВЎВ¦s use of symbolism defines the character of Roy Hobbs and shows how the events occurring
around him affected his decisions and, eventually, his career.
Symbolism in The Natural takes the form of characters, such as women who strongly influenced Roy; historical events, such as the infamous 1919
World Series scandal; and even Greek and Roman mythology. All forms of symbolism used by Malamud are woven into the life and career of Roy
Hobbs.
As a first example, women have a tremendous ... Show more content on Helpwriting.net ...
His desperate attitude leads him to be seduced by her, ending his bid to make the Chicago Cubs.
The character of Harriet Bird serves as an ancestor–figure to Iris Lemon and Memo Paris (Helterman 25). In a way, Iris and Memo are symbolic
descendants of Harriet because they, too, have so much influence on Roy. Memo, however, closely resembles Harriet in personality. Both of the
women are very attracted to two separate major league ball players, Memo having a relationship with RoyВЎВ¦s teammmate Bump Bailey, and Harriet
being attracted to Whammer Wabold on the train. Both also seem to want to cause Roy harm, doing what they can to stand in the way of his eventual
stardom.
The two truly opposite personalities created by Malamud are Memo and Iris (27). Physically, Memo is first shown wearing a black dress and has
red hair; Iris is shown wearing a red dress with a white rose attached and has black hair. Mentally, Memo tends to use her memory to live in the past,
relating everything to her deceased lover, Bump. On the other hand, Iris uses substance to live, describing her life with actions and words rather than
by memories. Malamud creates these two characters to force Roy to choose his fate. For his own benefit and well being, Roy should choose Iris and
stay away from Memo. MemoВЎВ¦s attractiveness and seductiveness, however, keeps Roy from making the right decision.
Another form of symbolism that influences RoyВЎВ¦s

Greek Language Essay
A survey on various platforms for Sanskrit and Part–Of–Speech Tagging Methods
Sulabh Bhatt, Parmar Krunal
Department Of Computer Science, Gujarat University
Ahmedabad, India sulabhbhatt@gmail.com parmar.krunal005@gmail.com
Abstract – In this paper we present a Natural language processing for Sanskrit using Different approaches. Sanskrit is a oldest and considered as the
mother of all languages. The Sanskrit, the world 's ancient language has got a wealthy grammar. The Sanskrit grammar text Ashtadhyayi is written
by Panini (an Indian Sage). Sanskrit is a well suitable language for providing an advanced artificial intelligence for Computers. Part of Speech (POS)
Tagging is the first step in the development of any NLP Application. A POS Tagger (POST) is a piece of software that reads text in some language
and assigns parts of speech to each word (and other token), such as noun, verb, adjective, etc.
Keywords – NLP for Sanskrit, Tagset, POS Tagging, HMM, CRF
I.INTRODUCTION
Natural language processing: Natural language is the embodiment of human cognition and human intelligence. Natural language processing (NLP) is a
cross disciplinary field in computer science and linguistics where a computer can generate and understand human speech. It is the ability of a computer
program to understand human speech as it is spoken. NLP is a component of artificial intelligence (AI).The development of NLP applications is
challenging because computers traditionally require humans to "speak"

Case Study On Neural Machine Translation
Facebook partnered with Bing in 2011 for translation services, making it an early pioneer in the move toward neural machine translation.
In December 2015, Facebook dropped Bing and began to outsource its translation services while developing its own translation technologies.
Facebook's own neural machine translator went fully operational on August 3, 2017.
Overview
Hello and thank you for your question about Facebook neural machine translation. The short version is that Facebook has been moving toward
integrating their own translation technology since 2011, and have recently (August 2017) gone fully operational with their own Neural Machine
Translator. Below you will find a deep dive of our findings.
METHODOLOGY
Our goal for this ... Show more content on Helpwriting.net ...
Facebook was an early pioneer of online translation when in 2011 it started using automated systems to translate users' posts and comments in the News
Feed. Facebook used Bing initially because they didn't yet have their own technology.
In January 2015, Facebook open–sourced Torch (their deep learning library). Facebook explains TORCH as an open source development environment
for numerics, machine learning, and computer vision. Many projects on machine learning and AI at FAIR (Facebook AI Research) use Torch.
Also in 2015, Facebook acquired Wit.ai, a startup using understanding of natural language in text/voice to power user interfaces.
In December 2015, Facebook dropped Bing and started using its own translation technology. The issue was that Bing was built to translate more
properly written website text, not human slang. Facebook stated that the disconnect between the languages people speak and the content they want to
connect to on the Internet is what made them want to create their own neural network–based machine translation (MT) system.
Also in Dec 2015, Facebook opensourced it's hardware designs for anyone to explore through the Open Compute Project. The server was called
BigSur, which is described as servers with graphics processing units (GPUs), which have become the chip of choice for deep learning.

Later, in June 2016, Facebook stated that Statistical

Semantic Theories Of Natural Language
This essay will discuss semantic theories of natural language. Emphasising on the use of meaning in language, the process of human thought in
language use and also how reality is an influence on language.
The Oxford Dictionaries(n.d) provide definitions of the key words in enquiry as follows. ("meaning.") " What is meant by a word, text, concept, or
action:" .
("thought.")"An idea or opinion produced by thinking, or occurring suddenly in the mind:".
("reality.") "The state of things as they actually exist, as opposed to an idealistic or notional idea of them: ".
It can be understood that the human language consists of words as spoken or in text as a concept or to define an action to correlate meaning.
With the words that are chosen to be ... Show more content on Helpwriting.net ...
David Hornsby (2007) claims "we have a mental dictionary or lexicon which stores the form of a lexeme". Hornsby 's claim is correct as in (??) Noam
Chomsky brought forward the idea of a "Language Acquisition Device".
Language is consistent among the reality shared among speakers rather than a surreal understanding of the world.
Identifying the meaning of our expressions on the basis of its truth conditions was introduced by David Donaldson (1967) with a theory of
truth–conditional semantics. It aims to define the semantics of natural language. Davidson expressed the idea that "language expresses meaning to be
true if it coheres with its truth conditions".
Include claims about truth conditional semantics
The truth–conditional theory defines meaning in language to be the same as the truth conditions of the proposition and .
(Donald Davidson **) Claims
DAVIDSON OPPOSES TO DEFINITIONS OF MEANING OF ENTITIES
It has never been proven that language dramatically shapes the way it's speakers think (Pinker, 48).
It can be said that a cognitive component of language is the language of thought that of which all humans use.
(**DATE) describes that the language of thought is
(Stephen Pinker **)

Slobin claims"There is a process of "thinking for speaking" in which cognition plays a dynamic role within the framework of linguistic expression:
Dan L. Slobin (??) describes a cognitive process, which he labelled "thinking for speaking" . This is the kind

Natural Language Processing ( Nlp )
CHAPTER1: INTRODUCTION
Natural Language Processing (NLP) deals with actual text element processing. The text element is transformed into machine format by NLP. Artificial
Intelligence (AI) uses information provided by the NLP and applies a lot of maths to determine whether something is positive or negative. Several
methods exist to determine an author's view on a topic from natural language textual information. Some form of machine learning approach is employed
and which has varying degree of effectiveness. One of the types of natural language processing is opinion mining which deals with tracking the mood
of the people regarding a particular product or topic. This software provides automatic extraction of opinions, emotions and sentiments in text and also
tracks attitudes and feelings on the web. People express their views by writing blog posts, comments, reviews and tweets about all sorts of different
topics. Tracking products and brands and then determining whether they are viewed positively or negatively can be done using web. The opinion
mining has slightly different tasks and many names, e.g. sentiment analysis, opinion extraction, sentiment mining, subjectivity analysis, affect analysis,
emotion analysis, review mining, etc.
However, they all come under the umbrella of sentiment analysis or opinion mining. Sentiment classification, feature based sentiment classification and
opinion summarization are few main fields of research predominate in sentiment analysis.
In

The And Temporal Information Extraction
Much of the information extraction community early focus on in tasks like named entity recognition, co–reference and relation extraction, but recently
due to the high demand of temporal information in different NLP application, scholars are focusing on event, temporal and event and temporal
information extraction and the extraction of event and temporal information became a hot research area. Different scholars involved in event and
temporal information extraction researches. Currently there are a lot of research conducted in event and temporal information extraction in different
domains and languages with different techniques, methods and tools. In this chapter, we present some of the works conducted in the English language
related to this thesis project. The first work we discuss is called TIE, Temporal Information Extraction system extracts events from text by inducing as
much as temporal information possible. TIE makes global inference, enforcing transitivity to bound the beginning and finishing time for each event.
TIE introduces temporal entropy as a method to evaluate the performance of temporal IE system. TIE system outperforms in experiment in three
optional approaches. The TIE system uses a probabilistic method to recognize temporal rations. They use TimeBank data [25] to train the system. TIE
processes, each natural language sentence into two sequential phases. The first phase is responsible for extracting event and identifying temporal
expression and it use a

We Propose A Novel Framework For Tweet Segmentation
Abstract–Twitter has become one of the most important communication channels with its ability providing the most up–to–date and newsworthy
information. Considering wide use of twitter as the source of information, reaching an interesting tweet for user among a bunch of tweets is
challenging. A huge amount of tweets sent per day by hundred millions of users, information overload is inevitable. For extracting information in large
volume of tweets, Named Entity Recognition (NER), methods on formal texts. However, many applications in Information Retrieval (IR) and Natural
Language Processing (NLP) suffer severely from the noisy and short nature of tweets. In this paper, we propose a novel framework for tweet
segmentation in a batch mode, called HybridSeg by splitting tweets into meaningful segments, the semantic or context information is well preserved
and easily extracted by the downstream applications. HybridSeg finds the optimal segmentation of a tweet by maximizing the sum of the stickiness
scores of its candidate segments. The stickiness score considers the probability of a segment being a phrase in English (i.e., global context) and the
probability of a segment being a phrase within the batch of tweets (i.e., local context). For the latter, we propose and evaluate two models to derive
local context by considering the linguistic features and term–dependency in a batch of tweets, respectively. HybridSeg is also designed to iteratively
learn from confident segments as pseudo

Theme Of Language Devices In The Joy Luck Club
In The Joy Luck Club, language devices such as figurative language, diction, sentence structure, and significant detail are used to characterize the
different characters in the book. These language devices capture the characters' emotions, personality, qualities of mind, and goals. Amy Tan uses a
variety of language devices to characterize Ying–ying's emotions of sorrow, disconnection, shame, love, her passive, careless personality, and her
quality of mind of determination.
The use of language devices creates Ying–ying's emotions of sorrow and her passive personality and quality of mind. Throughout the novel, Ying–ying
mentions that her daughter Lena and she are ghosts. The ghost becomes a symbol of passivity, a symbol of not taking action to stop bad things from
happening. The ghost symbol creates Ying–ying's voice by representing her passive personality and quality of mind. Additionally, the author uses
significant pieces of detail. In "The Moon Lady," Ying–ying gets lost. She observes her shadow and describes it, "It was shorter this time, shrunken
and wild–looking. We ran together over to some bushes along a walkway and hid" (80). This piece of detail shows a personality shift in Ying
–ying. It
describes the changes in Ying–ying's shadow which represents the change of her restless personality to a passive and silent one. Another language
device used is diction. When introducing "The Moon Lady," Ying–ying says, "And I want to tell her this: We are lost, she and I, unseen and not seen,
unheard and not hearing, unknown by others" (64). The words "unseen," "unheard," and "unknown" are related to one another at a certain level, and
they create a general picture of Ying–ying's emotion. Ying–ying feels anguish for not doing anything in her whole life and letting herself become a
ghost. The diction also reveals Ying–ying's anguish for letting her daughter become a ghost like herself.
Language devices capture Ying–ying's emotions of disconnection and her careless personality. Ying–ying starts to talk about her daughter Lena and the
effect her passive personality has on her. Ying–ying explains how she lived in America, accepting everything that came her way and how she accepted
Lena's American ways. She says,

Language As A Natural Language
In our society today, language plays a diverse role in human potential and captures individual unique human characteristics of expression. Likewise, if a
universal language was adopted, these distinctive perspectives will be lost. In correlation, linguistic and phonological skills were created when people
used language as a natural communication system. Consequently, one's daily life is impacted by language through unique ways we can communicate
to manifest problem–solving and cognitive skills. Above all, language plays a huge role in cooperation and sharing of ideas throughout the world.
Undeniably, English is considered the dominant language spoken today. However, as time passed, cultural identities became corrupted and other native
... Show more content on Helpwriting.net ...
Evidently, the base and growth of human intelligence is within the framework of language. In this case, language unfolds the social formation which
portrays the exchange of ideas, views, emotions, and value. As a result, complex grammatical skills are formulated to grasp greater communication
structure. In other words, the loss of linguistic diversity would be detrimental because every language has its own uniqueness that adds to our
scientific understanding of grammar and social skills. According to Grenoble, "If English were the only language on the face of the earth, we could not
know literally hundreds of things which are permitted, even predicted, by universal grammar and accidentally missing in English, or any other single
language." Clearly, there are many words and phrases that cannot be translated from one language to another. For that reason, the grammatical
principles of multilingualism have critical impact on how we interpret the need to form social groups and use diagnostic set of problem–solving skills
to identify how communication can be formed. To expand on that, "[g]rammar did not come from a set of rules that are somehow hard–wired into the
brain. It is more likely that humans needed to solve the social problem of ensuring that everyone understood each other" (Ceriani). In other words,
language can be learned

How Does Language Shape The Way We Think?
Nothing brings people together more than language. As an international student, I noticed that more often than not, international students tend to
befriend those with a common native language. Perhaps their common language makes it easier for them to communicate since they might not be
comfortable with speaking English. Another possibility would be that sharing a language can also mean that they share a common way of thinking.
Lera Boroditsky, an assistant psychology professor at Stanford University, wrote the article "How Does Our Language Shape the Way We Think?" to
illustrate to her readers that language, whether it is grammar or just the general logic, does indeed affect how we think. Boroditsky and research teams
in Stanford and MIT collected data from all over the world. Because of the extensive amount of research and her article's solid structure, I find
Boroditsky's argument easy to follow and understand, therefore quite convincing. She is so knowledgeable in her area that her arguments and article
are solid and build on top of each other like Tetris tiles. A well
–written article can only be achieved by knowing and understanding your material well.
The main reason that Boroditsky's argument that language shapes our minds is valid is that the research she did with her teams covers a wide variety
of aspects on this topic while still keeping her article cohesive. The first research Boroditsky introduces to her audience is the research on the Kuuk
Thaayorre, which is an

State of the Art in Multilingual Text Retrieval Accessing...
In this paper we surveyed the state of the art in multilingual text retrieval accessing parallel web pages. Multilingual search engines typically consist
of a crawler which traverses the web, retrieves the required web page in the desire languages. It provides front end user interface, which can be used
for selecting language for query submission. The way the query is fired leads into two types of search Cross–language information retrieval and
Multi–language information retrieval. In cross–language retrieval the user query is machine translated into multiple language queries automatically as
per user selection and then fired. In multi–language retrieval the user has to provide queries in multiple languages to fetch the web documents in
different languages. Also in some search engine the web page is machine translated and forwarded to the user. NLP is still in the expansion phase and
has to make advances in it, research is going on all over world. Experiment was done with top rated multilingual search engine to access parallel pages
but could not find it. When billions of parallel web documents are present on the web in different languages why not explore that? A alternative to that
can be searching through parallel pair finder.
Keywords: NLP,MT Machine Translation, CLIR Cross–language, information retrieval, Multilingual.
1. Introduction
The total number of languages in the world is between 5,000 and 10,000. In a country like India people speak about 57 different

Common Core Standards Literature Review
Literature Review What is the common core? "The Common Core State Standards (CCSS) defines the knowledge and skills in English language arts
and mathematics that students need for success in college and careers upon high school graduation" (Santos, Darling–Hammond, Cheuk (2012)). The
common core was created, "to provide clear academic benchmarks with more concise academic standards for essential learning that will prepare
students to be college and career ready" (Liebtag, E. (2013)). The common core standards have then, been introduced and applied to most schools in the
U.S, and although it may have its controversies, the major issue, is its effect on ELL (English Language Learners) students. "ELs currently constitute
10 percent of the U.S.... Show more content on Helpwriting.net ...
According to Duguay, A., Massoud, L., Tabaku, L., Himmel, J., & Sugarman, J. (2013, September), "As educators have examined the standards more
deeply, concerns have arisen about their implementation in classrooms with diverse groups of students, including English learners". Not only this, but
the concept of math also has its visible adversities. According to Robertson, K. (2009), "Although it is easy to assume that many English language
learners (ELLs) will excel in math because math is a "universal language" and students may have had prior educational experience that included
mathematical instruction, that assumption can lead educators astray". Many teachers are struggling with the, "increasingly rigorous grade–level
content instruction; by content area teachers, many of whom are newly incorporating language development techniques in their subject area classes"
(Duguay, A., Massoud, L., Tabaku, L., Himmel, J., & Sugarman, J. (2013, September)). The common core may be the stepping for detailed
curriculum, but it is seeming that, it "cannot be tailored to all of the diverse populations of our nation" (Liebtag, E. (2013)). The expectations of the
common core exacerbate the academics for ELL students. According to, HAKUTA, K., SANTOS, M., & FANG, Z. (2013), "when ELs are isolated for
direct language instruction,

Description Of Automatic Text Summarization
Automatic Text Summarization Bhavika S. Joshi Pooja N. Mane Atharva College of Engineering Atharva College of Engineering Department of
Computer Science Department of Computer Science University of Mumbai University of Mumbai Mumbai, IndiaMumbai, India Email:
bhavika.joshi1994@gmail.com Email: poojamaner2611@gmail.com Kaveri S. Metkari Atharva College of Engineering Department of Computer
Science University of Mumbai Mumbai, India Email: kaveri.metkari@gmail.com Abstract – Nowadays people want a quick, rapid and concise review
of any given text rather than going through the entire length of the content. In this growing age of information technology witty huge amount of data
being churned every second users for reliable context that is short and concise over lengthy paragraphs of text. Realizing this need this project is based
on summarizing content in to a more concise yet informative context without losing the moral premise or the objective for which the text was
originally developed. We employ various data mining algorithms to condense the entire text into a content rich summary document by extracting the
prominent and relevant information outlining the purpose of the entire text. I.

The Importance Of Natural Language In Hamlet In William...
"Something is Rotten in the state of Denmark" (Shakespeare, 1.5.1780) How much power does a king have? In Early Modern England this question
was not one of politics and militaries, but of a natural social order. The Great Chain of Being Places a King above his country; if the king becomes
corrupted so does the state and in turn, the natural world will become diseased and rank. Shakespeare's use natural language in hamlet indicates an
adherence to The Great Chain of Being. The corruption of the natural world is a metaphor for the corruption of the state by the perverse actions of
Claudius and Gertrude. These metaphors refer to corrupt animals and plants, to disease and death, and ultimately connect to the fall of man. Hamlet's...
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Disease and infection, pungent and potent, is caused by this "Murder most foul" (1.5.1781). This blight rests upon Claudius and Gertrude, and their
sin, disease, and disorder is conferred to Denmark. As the king and queen of Denmark, Claudius and Gertrude's actions directly influence their
domain. Hamlet reflects the great chain of being in this way, applying the rulers infections and guilt to Denmark. As Marcellus says, "Something is
rotten in the state of Denmark." This statement is more than an ill portent, but a judgement on a country led by rotten rulers. Like a weeds the sin
overtook the country. Like Gertrude's sexual depravity, "'tis an unweeded garden,/That grows to seed; things rank and gross in nature" (1.2.1772).
These references to environmental corruption illustrate the decay that results from moral pollution. Claudius and Gertrude's marital bed is already
cursed: as the Ghost says, "So lust, though to a radiant angel linked/Will sate itself in a celestial bed/ and prey on garbage." If the king and the queen
are dining on "garbage," the natural world must follow in turn. Hamlet describes crime and conspiracy in terms of weeds, "Repent what's past, avoid
what is to come/And

Difference Between Grammar And Generative Grammar
GRAMMAR Grammar was considered as one of the most important for the development of a language. It was defined as set of rules and regulations
for English language. There are many different types of grammar and they are, Comparative Grammar : Comparative grammar was defined as the
analysis and comparison of the grammatical structures of a language. Contemporary work in comparative grammar was concerned with "a faculty of
language that provides an explanatory basis for how a human being can acquire a first language. In this way, the theory of grammar was a theory of
human language and hence establishes the relationship among all languages". Generative Grammar The rules determining the structure and
interpretation of sentences that speakers accept as belonging to the language. "Simply put, a generative grammar is a theory of competence: a model of
the psychological system of unconscious knowledge that underlies a speaker's ability to produce and interpret utterances in a language". Mental
Grammar The generative grammar stored in the brain that allows a speaker to produce language that other speakers can understand. "All humans are
born with the capacity for constructing a Mental Grammar, given linguistic... Show more content on Helpwriting.net ...
The verb has eight simultaneous features: moods, kind, type, forms, number, person, tense, conjunction. There are five moods: indicating,
imperative, optative, subjunctive and infinitive. There are three kinds of actives, middle, and passive: active'I strike': passive 'I am struck' the
middle expression both activity and passitivity, the active is clearly distinct in form the middle/passive; the middle/passive are distinct formally only
in some form,'I was myself'. I do it for myself. There are three forms, simple compared and derivative (formed from a compound: the "derived" type is
formed from a simple form for

The Natural Language Processing ( Nlp )
INTRODUCTION Natural Language Processing (NLP): NLP is a process in which human makes communication with machine easily. NLP is related
to area of human and computer interaction. There are many application developed last few years. The very helpful application is that a machine take
instruction by human voice and follow operation on it. NLP are trying to make computer more reliable that are easier to use by people. So rather than
learn a special language of computer command, people will talk with computer in their own language. 1.1 MAJOR TASK IN NLP [b]: 1.1.1 Automatic
Summarization [b]: It work as the summary of a chunk of text. Like, article in political section in newspaper. 1.1.2: Machine translation [b]:
Automatically translate language from one human to another human. 1.1.4 Optical Character Recognition [b]: Optical Character Recognition is a
process mechanical or electronic conversion of scanned or photographic image of typewritten or printed text into machine encode or computer readable
text. 1.1.4 Speech recognition [b]: In speech recognition take a sound clip of the person and determine the textual representation of speech. 1.1.5
Speech segmentation [b]: In speech segmentation take a sound clip on the person and separate into words. 1.1.6 Word segmentation [b]: Word
segmentation takes the chunk of continuous text and separate words. 1.2 APPLICATION OF NLP [b]: Classify text into categories Index and search
large text Question answering Speech

Dynamic News Classification Using Machine Learning
Dynamic News Classification using Machine Learning Introduction Why this classification is needed ? (Ashutosh) The exponential growth of the
data may lead us to a time in future where huge amount of data would not be able to be managed easily. Text Classification is done through Text
Mining study which would help sorting the important texts from the content or a document to manage the data or information easily. //Give a
scenario, where classification would be mandatory. Advantages of classification of news articles (Ayush) Data classification is all about tagging the
data so that it can be found quickly and efficiently.The amount of disorder data is increasing at an exponential rate, so if we can build a machine
model which can automatically classify data then we can save time and huge amount of human resources. What you have done in this paper (all)
Related work In this paper [1] , the author has classified online news article using Term Frequency–Inverse Document Frequency (TF–IDF)
algorithm.12,000 articles were gathered & 53 persons were to manually group the articles on its topics. Computer took 151 hours to implement the
whole procedure completely and it was done using Java Programming Language.The accuracy of this classifier was 98.3 % . The disadvantages of
using this classifier was it took a lot of time due to large number of words in the dictionary. Sometimes the text contained a lot of words that described
another category since the

Trends Of E-Commerce Trends
Four Trends That Will Dominate the E–Commerce Industry In 2018 Every year the e–commerce industry is experiencing a stupendous 20% growth.
Last year has been awesome for the e–commerce industry. New technologies emerged at the end of 2016, flourished and evolved to bring about a
maturity in the entire online retail industry. Definitely, at the end of 2017, this evolved technology and few emerging technologies in the e–commerce
domain will be setting new trends for 2018. Build Your Online Store by Diving into the Happening E–commerce Trends of 2018 The technology
advances in 2018 have brought us where computers can easily augment human understanding and behavior. Moreover, e–commerce businesses are
trying hard to stand out today's noisy competition by making their online... Show more content on Helpwriting.net ...
Using AR and VR technology to develop an e–commerce website will involve customers deeply offering a compulsive 'Immersive' experience. So
hold on to your seats, tighten your seat belts and enjoy the ride to v–commerce because the e–commerce industry will be changing forever. Conclusion
The primary aim of every business is to acquire and retain customers; e–commerce business is no different. Each year technology evolves compelling
us to take a note of it. Coping up with these trends is beneficial for online businesses because early adoption of latest technology provides a leading
edge over the competition. Inversely neglecting new market and technology trends will eventually result in a major setback. It is hard to predict the
future concerning e–commerce technology. However, we think these four trends will particularly make an impact in 2018. Regardless of what you are,
selling online it is pretty clear that not a single e–commerce brand can afford to rest on its laurels. Therefore, it's your take whether to keep up with
these trends or

Gigi Acker Eating Smart At Work Case Study
In the wired world, Gigi the personal snack consultant is a wanted woman. Snacks That 'Amp–Up' Energy A Peek Into the Corporate Pantry Eating
Smart at Work Gigi Acker, R.D., is the nutritionist to the stars of Silicon Valley. She meets one
–on–one with employees at major West Coast tech
companies to teach them how to identify cravings, find healthy snacks that actually taste good and learn to time their eating to continuously energize
the body and brain. She works with personalities ranging from high–flying execs to grass–roots Web monkeys. When Gigi meets them, they're getting
tired and cranky during the workday and they don't know why. But they do know what they want: maximum energy and smarts for the whole 12–hour
(or more) day. Everyone... Show more content on Helpwriting.net ...
First, [the protein bar] gives you carbs and protein ... [with the Snickers] you're getting more fat; nuts are 75 percent fat. High–fat food makes you
sleepy if you eat too much of it. And the energy bar has fiber, which you're not going to find in peanut M&Ms – plus, they're made from whole oats
and dried fruits. There's a difference in how our body reacts to something wholesome vs. sugar, which our body reacts unpredictably to.
FOXNews.com: What are typical client schedules you work with? Acker: It varies. I have some who ... start the day really early. One client gets up at
5, she's at the corporate gym at 6 and is eating a low–fat breakfast at 7. She found that by 10 she was starving and eating what other people brought in,
heading to the candy jars ... it was so frustrating. So we looked at it: She needed a 10 o'clock snack to stay energized. For her, she wanted
convenience. FOXNews.com: Was she looking to lose weight too? Is that a common goal of your

Space Race Evolution
Even though the Earth has been around for a few billion years, it has been only 200,000 years when the first homo sapiens, modern human species,
came to existence. To put it into perspective, if the arm length represents the timeline, the shoulder is the Big Bang, the beginning of the finger nail is
when the dinosaurs existed, and the human start to become a possibility right around the tip of the finger. Even more astounding, industrialization
started only in the 1800s, which estimated 200 years to develop to the current society. The remarkable number is evidence to human extraordinary
intelligence and limitless capabilities to transform ambition into reality; however, any development will reach to a point where the growth is less
significant than it is used to be. This is referred as the law of diminishing return. Therefore, the research for a more advanced technology, Artificial
Intelligence, or AI, has become the new Space Race of the 21st century. Many... Show more content on Helpwriting.net ...
If human hadn't eaten the food the same way the ancestor of over a half million years ago did, which was to cook them first, it would have taken
more than nine hours of eating a day to power the brain. (15) Cooked foods are pre–digested, softer and easier to swallow, promoting complete
digestion and absorption of nutrients. The same idea applies with allowing AI to take over time consuming and difficult task. The impact that AI
brings far more than just direct consequences. With AI, people work less and can spend more time exercising, maintaining a balance between physical
and mental health, which prevents stress and lowers the suicide or crime rate. Others can volunteer and help people in need while some can spend
more time with their relatives. The smartest one after all is still humans. They design machines to do the hard work so they can have more time for

Natural Language Generation Essay
Natural Language Generation Abstract Natural language generation is a relatively new field in computer science. The two main questions to be
solved are "what to say" and "how to say it." What to say includes answering questions not specifically asked by the user, and remembering previous
statements made by the user and by the program itself. How to say it involves construction of logical sentences, use of pronouns, and sentence
fragments. When speech synthesis is used, it also involves producing intelligible word rhythm, emphasis, and pauses. A new, exciting extension of
speech synthesis is the inclusion of "emotion" in speech. User: ELIZA: Men are all alike In what way? They're always bugging us... Show more content
on Helpwriting.net ...
Natural language generation can also be used in some expert systems. Another application is in translation programs. It is probable that many new
applications will be developed as natural language programs are refined. The two main issues in natural language generation are determining what to
say, and determining how to say it. The issue of determining "what to say" quickly spills over into other areas of Artificial Intelligence, however, a
few issues are especially interesting. The basis of these issues is that natural language is so "natural" to users that they expect, or at least desire the
computer to "think" like a human. This causes users to use imprecise language when communicating with natural language systems. For example, the
following questions were typed to PLANES, which is a question and answer system delivering information regarding aircraft flights and maintenance:
1. I request the number of flight hours... 2. I need to know the number of flight hours... 3. Want number of flight hours... 4. Find the number of... 5.
Was any work performed on Plane 3... The user does not desire the literal interpretation of the above statements. Literal interpretation would be as
follows: 1) No response by the program: the user is making a statement about what he/she is doing: he/she is requesting information. 2) & 3) No
response by the program: the user is making statement about his personal desires. 4) No

Artificial Intelligent, Natural Language Processing
Abstract
We are living in a busy world. Everyone is trying to catchup with almost everything he can. As a result we all need our own persona assistant to help
us out everyday. But not everyone can afford it. Intelligent Personal
Assistant is the answer for them. Artificial Intelligent is improving fast. And taking advantage of it in our everyday life can make our life much easier.
It can mimic basic things like a human companion. In this paper we compared between currently popular Intelligent Personal Assistants. What they can
do and what they can not yet. Though they provide state of art features but there is still many field to make improvement, like improved natural
language processing so that we don't have to use some predefined keyword to get answer.
Chapter 1
Introduction
With the breakthrough of speech recognition, natural language processing, semantic web and machine learning we can safely say that the age of
Intelligent Personal Assistant(IPA) is upon us. A software agent that can do various task or service for a person is called Intelligent Personal Assistant.
It depend on user input, location information and various online sources for information about weather, traffic conditions, news etc. Currently there are
many of such agent is available for everyday use such as Google Now by
Google, Siri by Apple, Amazon Echo, Microsoft Cortana and Facebook's M.
The first fully functional IPA is Denise developed by NextOS formerly known as Guile3D. The company was founded

How Psychology Helps Us Understand the Concept of Language...
How Psychology Helps Us Understand the Concept of Language and Intelligence as Related to Human Beings
Psychology, the study of behaviour and mental processes concerns itself with the reasons organisms do what they do and how they behave in a
particular way, For example why acquired skills are not lost when learnt ; Why do children rebel against parents and, why humans speak, love and
fight each other. These examples of learning and behaviour are directly related tointelligence and language in human beings.
It is said that language, foresight, musical skills and other hallmarks of intelligence are connected through an underlying facility that enhances rapid
movements. To most observers, the essence of Intelligence is... Show more content on Helpwriting.net ...
Alfred Binet and Theodore Simon together developed a test called the ( Simon Binet Test ), to assess the ability of children's performance at school.
They developed a table used to compare the mental age of a child to the actual age to produce the concept of I.Q. The conclusion was that a particular
intelligent person often seem quick and capable of juggling many ideas at once.
Not to be outdone, Wechler developed intelligence scales for both adults and children (WAIS & WISC). The scales are in two parts VERBAL AND
PERFORMANCE, giving a clear picture of the person's IQ; by identifying their strength and weaknesses in specific areas .The information can be used
in planning individualized instruction programs.
To help us understand the nature side of intelligence versus the nurture side Psychologists Bouchard McGue (1981), and Harrell et al(1955) provided
us with correlations and comparisons . In the case of Bouchard and McGue the correlations thus provided were:
Identical twins reared apart.72
Identical twins reared together.86 compared to
Non–identical twins reared together .60
Siblings reared apart.47
Then child and natural parent.50 while.
Then child and adopted parent.19
These results appear to strongly support the nature issue.

Numerous studies show or emphasizes the influences that environmental factors have on Intelligence. Harrell et al (1955) compared two groups of
enormously

Introduction Of Natural Language Processing
INTRODUCTION TO NATURAL LANGUAGE PROCESSING
What is NLP?
Natural Language Processing can be defined as the use and ability of systems to process sentences in a natural language such as English, instead of
using a specialized artificial computer language such as C, C++ etc. The systems used for NLP are a digital computer which is similarly resemble to
mainframe and personal computers. The digital computer systems in this fifth generation possesses artificial intelligence technique and thus able to
process natural languages. Natural language is a more restricted subset of a human language; it cannot be thought of an actual language that possesses
ambiguities which computers could not sort out. Hence it is fair that "Human Languages grant aberration that natural language cannot grant." In a
larger view; Natural Language Processing includes signal processing or speech recognition, context reference issues and semantic analysis and
processing. Typical applications for Natural Language Processing include the following:
a) A good human computer interface that can translate from a natural language into a computer language and vice versa. A natural language system can
act as an interface to a database system. This technology is very useful for the blind people; that with the help of speech recognition interact with
computers.
b) A basic necessity is for a translation program that could convert from one human vocal language to another. This saves down the time for translation.
C)

Language And Poverty In The United States
Poverty
According to the U.S. Census Bureau, in the United States in 2006, the poverty rate for all individuals was 12.3%. For children under the age of 18,
the incidence of poverty was 17%, and for children under the age of 5, the rate as 20.4%. Poverty do not discriminate, is continuous and it work in
patterns. Poverty is the extension to which an individual does without resources. These resources can consist of financial, emotional, mental, spiritual,
physical, support systems, relationships, and knowledge of hidden rules .The lack of these resources affects the children development in the way they
analyzed and find a solution to real problems. Educators ought to understand how children with non–financial resources develop the roles of language,
the hidden roles, and the systems of support.
Teachers need to understand that ... Show more content on Helpwriting.net ...
The register of language helps children in their early years to develop the language from a limited use of words, to a casual language (characterized by
a 400–800 words vocabulary), and finally to talk with a formal language (standard sentence syntax and word choice of work and school). These
aspects of language affect the students that live in poverty because they do not have access to formal register at home. The lack of formal register
combined with a lack of vocabulary, the knowledge of sentence structure or adequate syntax affects the student to develop a good score and do well in
school. Second, the pattern of discourse helps the student to organize the information. In the formal register, the patterns of discourse help the student
to get straight to the point. However, the students that have not access to formal register, educators become frustrated with the tendency of these

Natural Language Processing And Machine Learning Techniques
The manuscript at hand presents a framework that implements Natural language processing (NLP) and machine learning techniques to extract
synthesis parameters of metal oxides from a large set of published articles. The manuscript also presents insights into the key synthesis parameters using
machine learning algorithms. NLP technique is of broad and current interest in many research areas and it is being extensively used to extract
information on a large scale, which is otherwise not feasible via manual exploration. In the field of chemistry/materials, NLP holds immense promise to
extract useful information the literature, such as extraction of materials properties, processes, and various synthesis details. However, NLP has not been
... Show more content on Helpwriting.net ...
I believe the current manuscript holds the merit to be published in a high–quality journal, and my recommendation is to accept the manuscript to be
published in Chemistry of Materials. The authors may want to address the following list of minor issues to further improve the manuscript: 1.Logistic
regression classifier is applied to distinguish paragraphs that are related to synthesis from other non–synthesis related paragraphs. Applying logistic
regression to classify the paragraphs is an elegant way to determine the synthesis details, however, it might have errors in the classification (95%
accuracy in the current manuscript). A simpler way to classify would be to search for section titles like 'Methods', 'Materials', 'Methods and materials',
etc., and then classify the text in this section as synthesis paragraphs. It will be worth considering this approach and comparing it with the logistic
regression approach. However, the former technique might not work if the search paper is a review article. 2.From the description presented in the
manuscript, it appears that the data is extracted from the paragraphs. However, there are articles where the information is presented in the form of
tables/figures. A discussion on the scope of data extraction from tables/figures would be of significant interest to the chemistry community as large
amount of chemical/materials data is published in this format. 3.It would be helpful to have an explanation of the

Text Analysis : Text Mining
Text mining sometimes known as text data mining often refers to the process of pulling out of interesting and non–trivial patterns of knowledge form a
semi or unstructured text document. Text mining can also serve as an extension of data mining or of data finding from a structures database. With text
mining it can be the same as data mining but with a bit more complexity, because they somewhat carry out the same processes and has the same
purpose, however with text mining the data is more unstructured rather that structured in the data files such as : (pdf, word, xml etc.). This is so
because most people store information in the form of text, it is believed that text mining can be greater than data mining, during recent years there
where a number of studies done which indicates that 80% of business information is stored in text format.
Text mining is an interdisciplinary field which involved retrieving information, text analysis, information extraction, clustering, categorization,
visualizations, database technology, machine learning and data mining.
Text mining can be of great help to different area where there are large amount of data/ information such as accounting( monthly reports),human
resource(employee reports),marketing(customer feedback) just to name a few . With text mining we don't just use it as a means of filter but it can
also be used for prioritizing emails based on their level of important
Differentiate between text mining, text analytics and data

Web Intelligence And Its Usefulness
Abstract
In the world of Information Technology (IT), there are many areas and disciplinary of research available and Web Intelligence (WI) is one of the
new sub disciplinary of Artificial Intelligence (AI) and Advanced IT. When AI and IT is implemented on web it defines WI. WI is used to develop
web – empowered system, Wisdom Web, Web Mining, web site automation, etc. In this paper, detail discussion is done on Web Intelligence and its
usefulness in developing intelligent web. Many literatures are also discussed related to the Web Intelligence and at the end challenges and problems
faced during the research in the area is also mentioned. This paper will provide the pathway to the researcher who want to perform research in the field
of Web Intelligence.
Keywords – Natural Language Processing, Web Intelligence, Artificial Intelligence, Advanced Information Technology
I.Introduction
In the era of Information Technology (IT) Web Intelligence (WI) represent new sub disciplinary for scientific research and development that explores
fundamental roles as well as practical impacts of Intelligence. T. Y. Lin and Yan
–Qing Zhang [2] have described Intelligence as" a specific set of mind
capabilities which allow the individual to use the acquired knowledge efficiently and to behave appropriately in the presence of new tasks and living
conditions". With the explosive growth of internet, wireless network, web database and wireless mobile devices implies intelligence on web. Y.Y. Yao,

Questions On Natural Language Processing
Introduction
1.1 Inspiration and Outline
Today in the world of information technology everyone is using internet to share and access data. But the data is in the form of natural language. And
as we all know that all natural languages have basic feature that it have ambiguity. It is something which can be understand in two or more ways, and
that depends on what situation it occurs. There are different types of ambiguities present in natural languages like lexical ambiguity, structural or
grammatical ambiguity, ambiguity of scope, pragmatic ambiguity etc. Among all these ambiguities, lexical ambiguity is generally present in natural
languages. This ambiguity can be defined as the ambiguity which occurs because a word has various meaning. So, to use information technology in
best way we need to eliminate ambiguity from the sentences with the help of tool called word sense disambiguation.
Word Sense Disambiguation (WSD) is a tool which computes the correct sence of ambiguious word in context which it occur. It is a main challenge in
Natural Language Processing(NLP) and it is considered an AI– complete problem. For example consider the sentence–аҐ¤ and ;g ,d vke ckr gSA vke
Qyks dk jktk gSA Here, the ambiguous word is vke which can be interpreted as 'common' or as 'mango' based on the situation in which it is said.
The problem of recognition of definite sense of given word seems to be simple. As human being simply identify the meaning of a word given on a
given context. But

American Sign Language ( Asl ) Is A Visual And Natural...
American Sign Language (ASL) is a visual and natural language. It is used widely by the members of the deaf community in the United States
(Valli & Lucas, 2000; Andrews, Leigh, & Weiner, 2004). About 90% of deaf children are born to hearing parents (DOH) (NIDCD, 2015). 10% of
deaf children are born to families with one or both deaf parents (DOD) (Mitchell & Karchmer, 2002). Deaf children of DOD will use ASL as their
primary language rather than spoken English or a different language such as Spanish, Chinese, or other than English (Mitchell & Karchmer, 2002).
Deaf families understand the importance of having language access early and their deaf children's vocabulary will be as big comparable to
hearing children who are learning a spoken language (Baker, 2010). Deaf children from DOD have full access to ASL whereas most deaf children
from DOH have limited access to ASL. Deaf children of DOH are typically not given the same early opportunity (Baker, 2010). Research suggested
that the first few years of the deaf child's life are the most crucial to a child's development of language skills and for establishing successful
communication (NIDCD, 2014). In Texas, there are nine hundred–eighty Early Childhood Education (ECE) programs that offer either full–day or
half–day pre–kindergarten programs (LBB, 2007). One of the ECE is the deaf education program for children who are deaf and hard of hearing. One
setting in the deaf education program is a public school setting. A

Research Methodology on Natural Language Processing
Research methodology on Natural Language Processing:
The main aim of this project is to research on the integration of "Natural Language Processing " and information systems engineering to enhance query
retrieval in natural language processing.
Defining a research methodology:
The definition of research methodology includes two parts:
–Research definition
–Methodology
Research:
It is defined as a thorough and organized query or investigation on a particular theme to revise or determine the facts, theories, applications and so on.
Methodology:
It is a system of methods followed by a particular discipline. Thus, research methodology is the way how a researcher performs research.
Uses of research methodology:
There are many ... Show more content on Helpwriting.net ...
[Gordhan Marshall, 1998]
Objective–1:
To study the concept of natural language processing and various features involved in it.
The above objective is fulfilled by initiating an exact design required for performing the research process. The research design illustrates the basic
understanding about the research (NLP) and various features.
Research strategies:
Normally, research methodology includes two strategies for performing research.
–Qualitative research
–Quantitative research
Quantitative research:
Quantitative research methods are utilized to study the natural phenomena. So, it includes survey methods, formal methods, and numerical methods.

Qualitative research:
Qualitative research methods are utilized to study the social and cultural phenomena. So it includes observation, participant observation (field work),
interview sessions, documents and texts and finally the researcher's imitations and feedback. [Myers, 2009]
Qualitative research is a technique of promoting research that stresses the quality according to the user's point of view and approaches. In depth
interviews and focus groups are best examples of qualitative research. [Laura Lake, 2009]
Objective–2:
To study various procedures involved in query evaluation of natural language processing
The above objective of the project is fulfilled by selecting a suitable strategy among all the available strategies. In this research methodology, the
researcher used

Wireless Voice Controlled (Natural Language Processing)

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