A ROBUST THREE-STAGE HYBRID FRAMEWORK FOR ENGLISH TO BANGLA TRANSLITERATIONkevig
Phonetic typing using the English alphabet has become widely popular nowadays for social media and chat services. As a result, a text containing various English and Bangla words and phrases has become increasingly common. Existing transliteration tools display poor performance for such texts. This paper proposes a robust Three-stage Hybrid Transliteration (THT) framework that can transliterate both English words and phonetic typed Bangla words satisfactorily. This is achieved by adopting a hybrid approach of dictionary-based and rule-based techniques. Experimental results confirm superiority of THT as it significantly outperforms the benchmark transliteration tool.
Synonymy is an important yet intricate linguistic feature in the field of lexical semantics. Using the 100 million-word British National Corpus (BNC) as data and the software Sketch Engine (SkE) as an analyzing tool, this paper explores the collocational behavior and semantic prosodies of near synonyms in virtue of, owing to, thanks to, as a result of, due to and because of. The results show that these near synonyms differ in their collocational behavior and semantic prosodies. The pedagogical implications of the findings are also discussed.
Transliteration by orthography or phonology for hindi and marathi to english ...ijnlc
e-Governance and Web based online commercial multilingual applications has given utmost importance to
the task of translation and transliteration. The Named Entities and Technical Terms occur in the source
language of translation are called out of vocabulary words as they are not available in the multilingual
corpus or dictionary used to support translation process. These Named Entities and Technical Terms need
to be transliterated from source language to target language without losing their phonetic properties. The
fundamental problem in India is that there is no set of rules available to write the spellings in English for
Indian languages according to the linguistics. People are writing different spellings for the same name at
different places. This fact certainly affects the Top-1 accuracy of the transliteration and in turn the
translation process. Major issue noticed by us is the transliteration of named entities consisting three
syllables or three phonetic units in Hindi and Marathi languages where people use mixed approach to
write the spelling either by orthographical approach or by phonological approach. In this paper authors
have provided their opinion through experimentation about appropriateness of either approach.
A New Approach: Automatically Identify Proper Noun from Bengali Sentence for ...Syeful Islam
More than hundreds of millions of people of almost all levels of education and attitudes from different country communicate with
each other for different using various languages. Machine translation is highly demanding due to increasing the usage of web
based Communication. One of the major problem of Bengali translation is identified a naming word from a sentence, which is
relatively simple in English language, because such entities start with a capital letter. In Bangla we do not have concept of small
or capital letters and there is huge no. of different naming entity available in Bangla. Thus we find difficulties in understanding
whether a word is a proper noun or not. Here we have introduce a new approach to identify proper noun from a Bengali sentence
for UNL without storing huge no. of naming entity in word dictionary. The goal is to make possible Bangla sentence conversion
to UNL and vice versa with minimal storing word in dictionary.
A ROBUST THREE-STAGE HYBRID FRAMEWORK FOR ENGLISH TO BANGLA TRANSLITERATIONkevig
Phonetic typing using the English alphabet has become widely popular nowadays for social media and chat services. As a result, a text containing various English and Bangla words and phrases has become increasingly common. Existing transliteration tools display poor performance for such texts. This paper proposes a robust Three-stage Hybrid Transliteration (THT) framework that can transliterate both English words and phonetic typed Bangla words satisfactorily. This is achieved by adopting a hybrid approach of dictionary-based and rule-based techniques. Experimental results confirm superiority of THT as it significantly outperforms the benchmark transliteration tool.
Synonymy is an important yet intricate linguistic feature in the field of lexical semantics. Using the 100 million-word British National Corpus (BNC) as data and the software Sketch Engine (SkE) as an analyzing tool, this paper explores the collocational behavior and semantic prosodies of near synonyms in virtue of, owing to, thanks to, as a result of, due to and because of. The results show that these near synonyms differ in their collocational behavior and semantic prosodies. The pedagogical implications of the findings are also discussed.
Transliteration by orthography or phonology for hindi and marathi to english ...ijnlc
e-Governance and Web based online commercial multilingual applications has given utmost importance to
the task of translation and transliteration. The Named Entities and Technical Terms occur in the source
language of translation are called out of vocabulary words as they are not available in the multilingual
corpus or dictionary used to support translation process. These Named Entities and Technical Terms need
to be transliterated from source language to target language without losing their phonetic properties. The
fundamental problem in India is that there is no set of rules available to write the spellings in English for
Indian languages according to the linguistics. People are writing different spellings for the same name at
different places. This fact certainly affects the Top-1 accuracy of the transliteration and in turn the
translation process. Major issue noticed by us is the transliteration of named entities consisting three
syllables or three phonetic units in Hindi and Marathi languages where people use mixed approach to
write the spelling either by orthographical approach or by phonological approach. In this paper authors
have provided their opinion through experimentation about appropriateness of either approach.
A New Approach: Automatically Identify Proper Noun from Bengali Sentence for ...Syeful Islam
More than hundreds of millions of people of almost all levels of education and attitudes from different country communicate with
each other for different using various languages. Machine translation is highly demanding due to increasing the usage of web
based Communication. One of the major problem of Bengali translation is identified a naming word from a sentence, which is
relatively simple in English language, because such entities start with a capital letter. In Bangla we do not have concept of small
or capital letters and there is huge no. of different naming entity available in Bangla. Thus we find difficulties in understanding
whether a word is a proper noun or not. Here we have introduce a new approach to identify proper noun from a Bengali sentence
for UNL without storing huge no. of naming entity in word dictionary. The goal is to make possible Bangla sentence conversion
to UNL and vice versa with minimal storing word in dictionary.
This is a slide that contains the information about Introduction of Syntax.
Lecturer : Budi Hamuddin, M.Esl
ENGLISH EDUCATION DEPARTMENT
FACULTY OF EDUCATION AND TEACHER’S TRAINING
LANCANG KUNING UNIVERSITY
n Part 1 of this assignment, you will discuss the proposal dev.docxherthaweston
n
Part 1
of this assignment, you will discuss the proposal developed by your small-group collaboration and relate it to the research methods and linguistics concepts examined in this course.
In
Part 2
, you will evaluate a claim about computer-mediated communication using what you've learned about what language is and how CMC is used.
Part 1 (2 paragraphs)
(1 sentence)
What is the research question in your collaboration?
(1 paragraphs)
Discuss the
linguistic
variables
and
social factors
investigated by your group,and the
research methods
you've chosen to use. To show substantial evidence of critical thinking, your responses must do more than simply identify that concepts appear within your project. Instead, aim to explain, expand, connect, compare, or contrast how the concept appears in your project with how we covered the concept in the course. Each module has a "Readings & Multimedia" page with the required resources; review those resources and use and cite them appropriately.
Linguistic variables:
Quote specific examples to demonstrate the variation in language that your group investigated and explain them. For example, if you were interested in meme grammar like Gawne and Vaughan were, you could quote "teh" and "the" as orthographic and phonetic differences. If you were interested in how sincerity is conveyed like Gunraj et al, you could quote "Sure" and "Sure." (with period" to examine the role of the period in sincerity online.
Social factors:
Explain what extralinguistic (outside of language) factors or dimensions are relevant to understanding the language variation in your project. Connect to t
he reading from Janet Holmes
. How do you anticipate that these factors would affect the results of the project, if you could carry out the investigation?
Research methods:
Explain what methods your project uses to investigate your research question, and explain why these methods were chosen. Use the required readings and multimedia from the course to make connections.
(Note: if you would prefer to change the methods your group suggested, explain what would you change them to, and why.)
(1 paragraph)
Review the VoiceThreads for other groups. Choose one that you feel you understand well and respond to the prompt below.
Give the title of the proposal you examined. Use your understanding of research methods described in the course to discuss potential complications of their methods: what would you change or improve about the methods, and why? You may also discuss likely results based on your own experiences with CMC.
Part 2 (1-2 paragraphs)
Naomi Baron, whose 2007 study of American undergraduates' texts and IMs we read about several weeks ago, described that research and other research on computer-mediated communication in her book
Always On.
She acknowledges something that John McWhorter also mentions in his TED talk, which is that sometimes people feel very negatively about online language and wh ...
How do we generate spoken words This issue is a fasci-natin.docxwellesleyterresa
How do we generate spoken words? This issue is a fasci-
nating one. In normal fluent conversation we produce two
to three words per second, which amounts to about four syl-
lables and ten or twelve phonemes per second. These words
are continuously selected from a huge repository, the men-
tal lexicon, which contains at least 50–100 thousand words
in a normal, literate adult person1. Even so, the high speed
and complexity of word production does not seem to make
it particularly error-prone. We err, on average, no more
than once or twice in 1000 words2. This robustness no
doubt has a biological basis; we are born talkers. But in ad-
dition, there is virtually no other skill we exercise as much as
word production. In no more than 40 minutes of talking a
day, we will have produced some 50 million word tokens by
the time we reach adulthood.
The systematic study of word production began in the
late 1960s, when psycholinguists started collecting and ana-
lyzing corpora of spontaneous speech errors (see Box 1).
The first theoretical models were designed to account for
the patterns of verbal slips observed in these corpora. In a
parallel but initially independent development, psycholin-
guists adopted an already existing chronometric approach
to word production (Box 1). Their first models were de-
signed to account for the distribution of picture naming la-
tencies obtained under various experimental conditions.
Although these two approaches are happily merging in
current theorizing, all existing models have a dominant kin-
ship: their ancestry is either in speech error analysis or it is
in chronometry. In spite of this dual perspective, there is a
general agreement on the processes to be modeled.
Producing words is a core part of producing utterances; ex-
plaining word production is part of explaining utterance
production3,4. In producing an utterance, we go from some
communicative intention to a decision about what infor-
mation to express – the ‘message’. The message contains one
or more concepts for which we have words in our lexicon,
and these words have to be retrieved. They have syntactic
properties, such as being a noun or a transitive verb, which
we use in planning the sentence, that is in ‘grammatical en-
coding’. These syntactic properties taken together, we call
the word’s ‘lemma’. Words also have morphological and
phonological properties that we use in preparing their syl-
labification and prosody, that is in ‘phonological encoding’.
Ultimately, we must prepare the articulatory gestures for
each of these syllables, words and phrases in the utterance.
The execution of these gestures is the only overt part of the
entire process.
This review will first introduce the two kinds of word
production model. It will then turn to the computational
steps in producing a word: conceptual preparation, lexical
selection, phonological encoding, phonetic encoding and
articulation. This review does not cover models of word
reading.
Two kinds of model ...
Recent approaches to arabic dialogue acts classificationscsandit
Building Arabic dialogue systems (Spoken or Written) has gained an increasing interest in the last few. For this reasons, there are more interest for Arabic dialogue acts classification task because it a key player in Arabic language understanding to building this systems. This paper describes the results of the recent approaches of Arabic dialogue acts classifications and covers Arabic dialogue acts corpora, annotation schema, utterance segmentation, and classification tasks.
Decoding word association 1 lexical dev within and mental lexicon for language 2Col Mukteshwar Prasad
Learning a language entails complex processes of learning, storing and accessing words within the mind. The mental space where this phenomena occurs has been called the mental lexicon.
The mental lexicon is a metaphor for the complex organizational system of the mind that allows learners to access information in a variety of ways.
All Indians do learn at least two languages one mother tongue and another English for job opportunities.Word Association Test is a Sub Conscious test in SSB. Hence understanding how these English words are stored in Mental Lexicon is important
This is a slide that contains the information about Introduction of Syntax.
Lecturer : Budi Hamuddin, M.Esl
ENGLISH EDUCATION DEPARTMENT
FACULTY OF EDUCATION AND TEACHER’S TRAINING
LANCANG KUNING UNIVERSITY
n Part 1 of this assignment, you will discuss the proposal dev.docxherthaweston
n
Part 1
of this assignment, you will discuss the proposal developed by your small-group collaboration and relate it to the research methods and linguistics concepts examined in this course.
In
Part 2
, you will evaluate a claim about computer-mediated communication using what you've learned about what language is and how CMC is used.
Part 1 (2 paragraphs)
(1 sentence)
What is the research question in your collaboration?
(1 paragraphs)
Discuss the
linguistic
variables
and
social factors
investigated by your group,and the
research methods
you've chosen to use. To show substantial evidence of critical thinking, your responses must do more than simply identify that concepts appear within your project. Instead, aim to explain, expand, connect, compare, or contrast how the concept appears in your project with how we covered the concept in the course. Each module has a "Readings & Multimedia" page with the required resources; review those resources and use and cite them appropriately.
Linguistic variables:
Quote specific examples to demonstrate the variation in language that your group investigated and explain them. For example, if you were interested in meme grammar like Gawne and Vaughan were, you could quote "teh" and "the" as orthographic and phonetic differences. If you were interested in how sincerity is conveyed like Gunraj et al, you could quote "Sure" and "Sure." (with period" to examine the role of the period in sincerity online.
Social factors:
Explain what extralinguistic (outside of language) factors or dimensions are relevant to understanding the language variation in your project. Connect to t
he reading from Janet Holmes
. How do you anticipate that these factors would affect the results of the project, if you could carry out the investigation?
Research methods:
Explain what methods your project uses to investigate your research question, and explain why these methods were chosen. Use the required readings and multimedia from the course to make connections.
(Note: if you would prefer to change the methods your group suggested, explain what would you change them to, and why.)
(1 paragraph)
Review the VoiceThreads for other groups. Choose one that you feel you understand well and respond to the prompt below.
Give the title of the proposal you examined. Use your understanding of research methods described in the course to discuss potential complications of their methods: what would you change or improve about the methods, and why? You may also discuss likely results based on your own experiences with CMC.
Part 2 (1-2 paragraphs)
Naomi Baron, whose 2007 study of American undergraduates' texts and IMs we read about several weeks ago, described that research and other research on computer-mediated communication in her book
Always On.
She acknowledges something that John McWhorter also mentions in his TED talk, which is that sometimes people feel very negatively about online language and wh ...
How do we generate spoken words This issue is a fasci-natin.docxwellesleyterresa
How do we generate spoken words? This issue is a fasci-
nating one. In normal fluent conversation we produce two
to three words per second, which amounts to about four syl-
lables and ten or twelve phonemes per second. These words
are continuously selected from a huge repository, the men-
tal lexicon, which contains at least 50–100 thousand words
in a normal, literate adult person1. Even so, the high speed
and complexity of word production does not seem to make
it particularly error-prone. We err, on average, no more
than once or twice in 1000 words2. This robustness no
doubt has a biological basis; we are born talkers. But in ad-
dition, there is virtually no other skill we exercise as much as
word production. In no more than 40 minutes of talking a
day, we will have produced some 50 million word tokens by
the time we reach adulthood.
The systematic study of word production began in the
late 1960s, when psycholinguists started collecting and ana-
lyzing corpora of spontaneous speech errors (see Box 1).
The first theoretical models were designed to account for
the patterns of verbal slips observed in these corpora. In a
parallel but initially independent development, psycholin-
guists adopted an already existing chronometric approach
to word production (Box 1). Their first models were de-
signed to account for the distribution of picture naming la-
tencies obtained under various experimental conditions.
Although these two approaches are happily merging in
current theorizing, all existing models have a dominant kin-
ship: their ancestry is either in speech error analysis or it is
in chronometry. In spite of this dual perspective, there is a
general agreement on the processes to be modeled.
Producing words is a core part of producing utterances; ex-
plaining word production is part of explaining utterance
production3,4. In producing an utterance, we go from some
communicative intention to a decision about what infor-
mation to express – the ‘message’. The message contains one
or more concepts for which we have words in our lexicon,
and these words have to be retrieved. They have syntactic
properties, such as being a noun or a transitive verb, which
we use in planning the sentence, that is in ‘grammatical en-
coding’. These syntactic properties taken together, we call
the word’s ‘lemma’. Words also have morphological and
phonological properties that we use in preparing their syl-
labification and prosody, that is in ‘phonological encoding’.
Ultimately, we must prepare the articulatory gestures for
each of these syllables, words and phrases in the utterance.
The execution of these gestures is the only overt part of the
entire process.
This review will first introduce the two kinds of word
production model. It will then turn to the computational
steps in producing a word: conceptual preparation, lexical
selection, phonological encoding, phonetic encoding and
articulation. This review does not cover models of word
reading.
Two kinds of model ...
Recent approaches to arabic dialogue acts classificationscsandit
Building Arabic dialogue systems (Spoken or Written) has gained an increasing interest in the last few. For this reasons, there are more interest for Arabic dialogue acts classification task because it a key player in Arabic language understanding to building this systems. This paper describes the results of the recent approaches of Arabic dialogue acts classifications and covers Arabic dialogue acts corpora, annotation schema, utterance segmentation, and classification tasks.
Decoding word association 1 lexical dev within and mental lexicon for language 2Col Mukteshwar Prasad
Learning a language entails complex processes of learning, storing and accessing words within the mind. The mental space where this phenomena occurs has been called the mental lexicon.
The mental lexicon is a metaphor for the complex organizational system of the mind that allows learners to access information in a variety of ways.
All Indians do learn at least two languages one mother tongue and another English for job opportunities.Word Association Test is a Sub Conscious test in SSB. Hence understanding how these English words are stored in Mental Lexicon is important
Similar to Teenagers’ short message service (sms) (20)
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Monitoring Java Application Security with JDK Tools and JFR Events
Teenagers’ short message service (sms)
1. TEENAGERS’ SHORT MESSAGE SERVICE (SMS) STYLES A PAPERPresented to the Academy of Foreign Language BinaSaranaInformatikaIn Partial Fulfillment of the Requirements for Diploma Three (D.III) Programme ByNOVI ERNAWATI31080024 English Department The Academy of Foreign Language BinaSaranaInformatika Jakarta 2011
2. CHAPTER I : INTRODUCTION Chapter 1 1.1. Background and Reason of Choosing the Title Language is means of communication. Transferring information between humans. The way someone communicate to one another depends on how close the relationship among them. Technology application makes the flow of information limitless. In terms of efficiency, the information may be shortened as long as it is understood by other persons involved in the communication. SMS use is may be the answer of teens to share information. Teens build their SMS styles. Short message service (SMS) is a technology that enables the sending and receiving of messages between mobile phone. More practical, cheaper and easier compared to cost when dialing someone. Teenagers can send a text a message more than 50 short message service (SMS) per days. Most of teenagers create styles writes to a text message and it become habitual and characteristic to send a text message. Styles as is written by teenagers are very unique with kind of styles. Of all these facts, analyzing teens’ SMS styles is such an interesting thing to conduct.
3.
4.
5. Chapter 2 2.1. Morphology Brinton (2000:33), Morphology is the study of the structure or form of words in a particular language, and of their classification. Carstairs-McCharthy, Booij and Brinton have the same opinion that used structure of word or patterns to technical of language called morphology. Morphology has word formation processes, and language users may also make new words by means of word creation (or word manufacturing). The following types can be distinguished like acronyms, blending, clipping, coinage, compounding, back formation, truncation, and contraction.
6. 2.1.1. Acronyms Chapter 2 Booij(2005:35) stated that combination of initial letters of a word sequence is called acronyms. For example, NATO > North Atlantic Treaty Organization, UP > Young Urban Professional. Lieber (2009:66) said that in acronyms, the new word is pronounced as a word, rather than as a series of letters. For example, Acquired Immune Deficiency Syndrome gives us AIDS, pronounced [eidz]. According to Aarts and McMahon (2006:510), an acronym is an initials which is pronounced according to ordinary grapheme-phoneme conversion rules. For example, AIDS >Acquired Immune Deficiency Syndrome pronounced[eidz], BASIC > Basic All-purpose Symbolic Instruction Code, EFTPOS > Electronic Funds Transfer at Point of Sale, LASER > Light Amplification by Stimulated Emission of Radiation, SALT > Strategic Arms Limitation Talks, SCUBA > Self-contained Underwater Breathing Apparatus, TESOL [‘ti:sal] > Teaching of English to Speakers of other Languages, UNESCO > United Nations Educational, Scientific and Cultural Organization are acronyms. Booij, Lieber, Aarts and McMahon agree that acronyms initially capitalized of a word and pronounced as a word.
7. 2.1.2. Blending Chapter 2 Arabi(2008:14) stated that another category of abbreviations in which the first syllables of two or three words are combined and pronounced as an ordinary word, such as codec > coder-decoder, modem > modulator-demodulator, inmarsat > international maritime satellite organization. Other forms of blending are made of the first syllable of the first word and the last syllable of the second word, such as netiquette > network-etiquette, webinar-web-based seminar. According to Booij (2005:41), blending is quite popular as a means of creating new English words. Try to come up with some meaning for the following recent blends, such as: fallowed, graffiti, metro sexual, nicotine, and padlock. In more details, blending combination of the first part of one word with the second part of another. Brinton (2000:120) said that a blend involves two processes of word formation, compounding and clipping. Two free words are combined and blended, usually by clipping of the end of the first word and the beginning of the second word, although sometimes one or the other morpheme is left intact. Blends are sometimes called “portmanteau” words. Brinton added that blending as a process a word formation overwhelm compounding and clipping. Arabi, Booij and Brinton agree that blending deal with word formation through combining parts of word to create a new word.
8. 2.1.3. Clipping Chapter 2 According to Brinton (2000:121-122), a clipping is the result of deliberately dropping part of a word, usually either the end or the beginning, or less often both, while retaining the same meaning and same word class. As in the following example: mimeo > mimeograph, fax > facsimile, burger > hamburger, flu > influenza etc.In more details, Brinton clearly clipping is generally not sensitive to morphological boundaries, though it does usually reflect phonological processes, selecting the longest possible syllable, what is called a maximal syllable. Such as, narc rather than nar. clipping often begin life as colloquial forms, such as the clipped forms prof > professor, gym > gymnasium, chem. > chemistry, psych > psychology, or lab > laboratory one hears on campus, but many have become fully accepted in the standard language and are no longer recognized as clipped forms. Arabi (2008:14) said that a category of abbreviations in which some of the letters or sounds of a word are omitted on the key letters are combined, for instance: bldg> building, mux > multiplexer etc. Lieber (2009:66) stated that clipping is a means of creating new words already existing words. For example, we have info created from information, blog created from web blog, or fridge created from refrigerator. Brinton, Arabi and Lieber have the same idea that abbreviation some words or sounds of a word which omitted the real meaning called clipping.
9. 2.1.4. Coinage Chapter 2 Smith (2009:19) said that closed-class words cannot be joined readily by new coinages; they form a restricted set of forms which play important cohesive roles in discourse. They are sometimes known as ‘grammar words’, a rather confusing description which will be generally avoided here. According to Lieber (2009:211), a word that is made up from whole cloth rather than by affixation, compounding, conversion, blending, reduplication, or other processes. Lieber added that coinage as a process a word formation rather than affixation, compounding, conversion, blending, reduplication and other process. Smith and Lieber agree that made up a new word with closed-class words, a process called coinage.
10. 2.1.5. Compounding Chapter 2 Smith (2009:184) stated that a process of lexical morphology (word-formation), where by derived forms are produced by placing two free morphemes together. Booij (2005:90) said that in many languages, compounding (also called composition) is the most frequently used way of making new lexemes. Its defining property is that it consists of the combination of lexemes into larger words. In simple cases, compounding consists of the combination of two words, in which one word modifies the meaning of the other, the head. This means that such compounds have a binary structure. Smith and Booij expressed that compounding deal with word formation with consist of the combination of two words.
11. 2.1.6. Back Formation Chapter 2 Booij(2005:55) stated that a prototypical case of paradigmatic word-formation is back formation in which the direction of derivation is inverted: the less complex word in derived from the more complex word by omitting something. For instance, sculpt > sculptor, babysit > babysitter etc. According to Lieber (2009:198), a morphological process in which a word is formed by subtracting a piece, usually an affix, from a word which is or appears to be complex. In English, for example, the verb peddle was created by back formation from peddler (originally spelled speddlar). According to Brinton (2000:120), in back formation speakers derive a morphologically simple word from a form which they analyze, on the basis of derivational and inflectional patterns existing in English, as a morphologically complex word. Booij, Lieber and Brinton agree that word formed in derived from complex words by omitted something.
12. 2.1.7. Truncation Chapter 2 Booij(2005:36) stated that linguists also use the term truncation. Especially in relation to the formation of personal names which have an affective load and faction as hypocoristic (names of endearment). In many cases, the stressed syllable of the full form is the core of the truncated name, which consists of one or two syllable. According to Arabi (2008:14), a category of abbreviations in which a word is simply shortened by cutting off the first or last syllable, such as phone > telephone, amp > amplifier, fig > figure. For building such short forms, it is recommended to select at least three letters of the word. Booij and Arabi expressed that truncation is a simply word in which omitted several words and consist of one or two syllable.
13. 2.1.8. Contractions Chapter 2 Arabi(2008:15) stated that a category of abbreviations in which the first and last letters of a word is selected, such as Mr > Mister, Dr > Doctor. Aarts and McMahon (2006:533) said that the status of ‘weak’ auxiliaries is somewhat less settled. Some descriptions treat contractions such as I’m, we’ll and she’s as reductions of the corresponding strong forms I am, we will and she has/is, whereas others recognize parallel inventories of strong and weak auxiliaries. Arabi, Aarts and McMahon expressed that a word formation in which become abbreviation one or two word and form from weak auxiliaries.
14. 2.2. Definition of Short Message Service (SMS) Chapter 2 Hillebrand(2010:28) stated that the short message service (SMS) as a very special type of messaging implemented as an integral part of the signaling systems, was proposed in GSM as the only new service that did not already exist in public networks. In more details, Hillebrand clearly the long existing idea of an enhanced paging service integrated into the new mobile communication system could be realized by the short message service (SMS) ‘point-to-point, mobile terminated’. Jonack(2004:14) said that short message service is a very clever and economical resource that was designed back in the 1980s when GSM specifications were taken from CNET (the research center of France Telecom) and redeveloped as a worldwide standard. According to Fulton and Fedricks (2010:255), SMS (short message service) text messages are another form of instant communication. SMS text messages can contain only 160 characters. Instant messages, by contrast, are not typically limited in length, and they can contain more than text, unlike SMS text messages which are text only. SMS is designed to be sent between cell phones, or from a PC to a cell phone. Hillebrand, Jonack, Fulton and Fedricks stated that short message service (SMS) is the new mobile communication system which easier, cheaper and practicial using SMS text messages with writes point to point or mobile terminated. Short message service (SMS) is designed to be sent between mobile phone.
15. CHAPTER III : DISCUSSION Chapter 3 3.1. SMS Styles There are some short message service (SMS) styles usually used by teenagers. Those styles become habits for us. They used short message service (SMS) for communication with their friends via mobile phone. When they communication used short message service (SMS), they apply some styles. Commonly, these styles understood to each others. There are some short message service (SMS) styles usually understood by teenagers. For example, acronyms, blending, clipping, coinage, compounding, back formation, truncation, and contraction. The next, there are some example short message service (SMS) here agreement with those styles. Which is supported by data in short message service (SMS) myself and I require some short message service (SMS) to my friends because for try complete short message service (SMS) styles. In analysis later the words of abbreviation here will bolt and italic so that more clear and easier understand with look at those short message service (SMS), which the words included acronyms, blending, clipping, coinage, compounding, back formation, truncation, and contraction.
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17. I’ll not do my homwrktmrrow. This short message service (SMS) received on June 9, 2011 at 10.26. There are some short message service (SMS) styles in this message. For example, I’ll include contraction, homwrk include compounding and tmrrow include clipping. Sist, do u free tomorrow morning? I want 2 ask u 2 join with me 2 have brunch at 10.30 a.m. at our favorite café. Would u sist? This short message service (SMS) received on June 5, 2011 at 20.07. There are some short message service (SMS) styles in this message. For example, sist include truncation, u and 2 include clipping, brunch include blending and a.m. include acronyms. Morning, have a gud day GBUfrens. This short message service (SMS) receive on June 4, 2011 at 10.20. There are some short message service (SMS) styles in this message. For example, gud and frensinclude clipping, GBU include acronyms. Friends, happy b’day, wish u all the best, thing in ur life. This short message service (SMS) receive on June 6, 2011 at 9.25. There are some short message service (SMS) styles in this message. For example, b’day and ur include clipping, WYATB include acronyms. Yesterday, ICU in front of trader a newspaper in station. U wears blue clothes. Is that u girl? This short message service (SMS) receive on June 6, 2011 at 16.41. There are some short message service (SMS) styles in this message. For example, ICU include acronyms and u include clipping. Chapter 3
18. I have modem, I use speedy modem, I think it’s faster than other modem, it’s from Telkom, and sometimes it needs time to connect to the internet but I think it’s enough for me. There are 3 wires on that modem black, yellow, n grey. It has different function, by the way I like using this kinda modem. This short message service (SMS) received on June 9, 2011 at 8.55. There are some short message service (SMS) styles in this message. For example, modem include blending, it’s include contraction, BTW include acronyms. Guys, at BSI any hotspot area, so you can browse. At Detos too any Wi-Fi zone, so we can browsing, just bring your net book or blackberry. This short message service (SMS) received on June 9, 2011 at 8.59. There are some short message service (SMS) styles in this message. For example, BSI include acronyms, WI-FI include blending and net book include compounding. I’ll be arriving at station at usual place. C u 2morrow. This short message service (SMS) received on June 4, 2011 at 13.55. There are some short message service (SMS) styles in this message. For example, I’ll include contraction and c u 2morrow include clipping. I thnk, he’s not a pick pockt like u say bfore. This short message service (SMS) received on June 9, 2011 at 10.40. There are some short message service (SMS) styles in this message. For example, he’s include contraction, pick pockt include compounding, u and bfore include clipping. Chapter 3
19. Chapter 3 I cannottypewrite now, bcause I so buzy. This short message service (SMS) received on June 12, 2011 at 7.19. There are some short message service (SMS) styles in this message. For example, cannot include contraction, typewrite include back formation, bcause and buzy include clipping. Are ukidd? This short message service (SMS) received on May 28, 2011 at 2 o’clock. There are some short message service (SMS) styles in this message. For example, u include clipping and kidd include truncation. R.A Kartini is my favrite Indonesian fig. This short message service (SMS) received on May 28, 2011 at 2 o’clock. There are some short message service (SMS) styles in this message. For example, favrite include clipping, and fir include truncation.
20. 3.3. Variations Several variations short message service (SMS) styles usually finded by message presented here. Beiby, beb - baby C, cee - see Luv, luph, lope, lov3, lop3 - love Hpyb’day, ppyb’day, happy b’day, hb – happy birthday Dunno - don’t know Wht, wat – what R, re, ar – are Tmrrow, 2morrow, tmrrw, 2morro – tomorrow Frens, flend, frenz - friend Thx, thnx, thankz, thengs - thanks Bcoz, coz, bcause, cuz – because Gud – good Bfore, b4 – before To – 2 N – and U - you Chapter 3
21. CHAPTER IV : CONCLUSION AND SUGGESTION Chapter 4 4.1. Conclusion Referring to what have been discussed in the previous chapter, it is reasonable to present such a conclusion here. Short message service (SMS) styles are usually used by teenagers to communicate or share such information to their friends. They share it via cell-phone. They unfold and apply new styles so that they may have the same comprehension and understanding one to another. The more they send messages, the more they apply different styles. As there are eight styles of SMS, clipping poses as the most style often used by teenagers, followed by acronyms, and the least is coinage. There are 11 SMS with clipping, 9 for acronyms, 8 for contraction, 7 for truncation, 5 for blending, 4 for compounding, 4 for back formation, 2 for coinage. There is also another finding about SMS style, here called as “variants”. It refers to a lexical word but it could be presented in many forms. As referred to data obtained, it is classified into clipping, but nor for other SMS styles. Teenagers have their own reason for applying SMS while they communicate with their friends and someone else. Teenagers more choose short message service (SMS) for communicate because it is cheaper, easier and more practical, and not spending much money. Teenagers commonly communicate more than 50 short message service (SMS) per days. This may also be influenced by the provision of free SMS from provider. There are several providers which give free SMS with special requirements, such sending 2 SMS will get 50 free SMS. This all will make teenagers possible to choose using SMS to communicate with someone else. They apply all kinds of SMS styles uniquely like clipping, acronyms, contraction, blending, coinage, compounding, back formation, and truncation.
22. 4.2. Suggestion Based on the conclusion above and realizing the importance of this topic, then I finally present several suggestions, as following: Before choosing the topic to be conducted in your research, you must be acquainted enough with information about the topic so that you will not confuse with your chosen. If you want to do analysis on the obtained data, it would be better if you prepare for needed materials to complete it, such as relevant references, literary reviews, and others supporting materials. These all will be helpful the time you conduct the analysis. Finding some examples on short message service (SMS) styles may also be helpful to make you be more familiar to the topic plan to be discussed. Enriching your data may also be gained by asking your friends’ SMS. By doing this, you may know more about the SMS styles applied recently among teenagers. Technology is vastly developed, and the use of SMS to communicate will be more flourish especially among teenagers, so the style of SMS may be richer. So, further discussion on this topic is widely opened. Chapter 4