This presentation summarizes research on code-switching in virtual communication in Bangladesh. The research surveyed 21 participants and found that over half switch between languages 5-10 times per day on social media. Most believe code-switching is beneficial for communication. While code-switching is becoming more common, ensuring it develops properly remains a challenge.
LEARNING CROSS-LINGUAL WORD EMBEDDINGS WITH UNIVERSAL CONCEPTSijwscjournal
Recent advances in generating monolingual word embeddings based on word co-occurrence for universal languages inspired new efforts to extend the model to support diversified languages. State-of-the-art methods for learning cross-lingual word embeddings rely on the alignment of monolingual word embedding spaces. Our goal is to implement a word co occurrence across languages with the universal concepts’ method. Such concepts are notions that are fundamental to humankind and are thus persistent across languages, e.g., a man or woman, war or peace, etc. Given bilingual lexicons, we built universal concepts as undirected graphs of connected nodes and then replaced the words belonging to the same
graph with a unique graph ID. This intuitive design makes use of universal concepts in monolingual corpora which will help generate meaningful word embeddings across languages via the word cooccurrence concept. Standardized benchmarks demonstrate how this underutilized approach competes SOTA on bilingual word sematic similarity and word similarity relatedness tasks.
LREC 2014 - Out in the open: Finding and categorising errors in the lexical s...Matt Shardlow
The slides I presented as part of the main conference of LREC 2014. If you're reading this beforehand then come along and see me talk in the flesh. Otherwise come find me and say hello.
LEARNING CROSS-LINGUAL WORD EMBEDDINGS WITH UNIVERSAL CONCEPTSijwscjournal
Recent advances in generating monolingual word embeddings based on word co-occurrence for universal languages inspired new efforts to extend the model to support diversified languages. State-of-the-art methods for learning cross-lingual word embeddings rely on the alignment of monolingual word embedding spaces. Our goal is to implement a word co occurrence across languages with the universal concepts’ method. Such concepts are notions that are fundamental to humankind and are thus persistent across languages, e.g., a man or woman, war or peace, etc. Given bilingual lexicons, we built universal concepts as undirected graphs of connected nodes and then replaced the words belonging to the same
graph with a unique graph ID. This intuitive design makes use of universal concepts in monolingual corpora which will help generate meaningful word embeddings across languages via the word cooccurrence concept. Standardized benchmarks demonstrate how this underutilized approach competes SOTA on bilingual word sematic similarity and word similarity relatedness tasks.
LREC 2014 - Out in the open: Finding and categorising errors in the lexical s...Matt Shardlow
The slides I presented as part of the main conference of LREC 2014. If you're reading this beforehand then come along and see me talk in the flesh. Otherwise come find me and say hello.
An Empirical Study on Comment Classificationijtsrd
Due to increasing technologies in the interactive web applications, there has been a lot of development in E commerce and online social networking activities. The comments or the post always plays a vital role in understanding of the attitude towards a particular topic, product of the online users. Most of the times these comments or posts help the other users to understand the scenario and to take the right decision on the web platform. Machine learning plays a vital role to understand and to estimate the accurate semantics of these posts and comments. Natural language processing is widely used for this, Most of the times natural language processing does not yield much expected results in the classification of these comments due to the complexity in the narration. These complexities generally arise either due to poor narration of the comments or highly sarcastic contents in the comments. So to overcome these problems this paper broadly studies all the past work on comment classification and try to find the new way of machine learning to get the highly classified labels of the comments. Shubham Derhgawen | Rajesh Tak | Subhasish Chatterjee "An Empirical Study on Comment Classification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28053.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/28053/an-empirical-study-on-comment-classification/shubham-derhgawen
Identification of monolingual and code-switch information from English-Kannad...IJECEIAES
Code-switching is a very common occurrence in social media communication, predominantly found in multilingual countries like India. Using more than one language in communication is known as codeswitching or code-mixing. Some of the important applications of codeswitch are machine translation (MT), shallow parsing, dialog systems, and semantic parsing. Identifying code-switch and monolingual information is useful for better communication in online networking websites. In this paper, we performed a character level n-gram approach to identify monolingual and code-switch information from English-Kannada social media data. We paralleled various machine learning techniques such as naïve Bayes (NB), support vector classifier (SVC), logistic regression (LR) and neural network (NN) on English-Kannada code-switch (EKCS) data. From the proposed approach, it is observed that the character level n-gram approach provides 1.8% to 4.1% of improvement in terms of Accuracy and 1.6% to 3.8% of improvement in F1-score. Also observed that SVC and NN techniques are outperformed in terms of accuracy (97.9%) and F1-score (98%) with character level n-gram.
Content out of 70MetCommentsCreate a short Microsoft® .docxmaxinesmith73660
Content: % out of 70%
Met?
Comments
Create a short Microsoft® PowerPoint® presentation or video that includes the following:
· personal background of the person interviewed (10%)
· where the person have lived (10%)
· any intersting cultural facts in the person’s history (15%)
· any experiences this person had adapting to new cultures (15%)
· a comparison of your cultural experiences with those of the individual interviewed (20%)
Style: % out of 10%
Did your slides utilize white space and avoid having too dense text?
Were your slides designed to be visually pleasing?
Mechanics: % out of 20%
Did you include speaker’s notes in your PowerPoint? They should be the majority of your presentation
Rules of grammar, usage, and punctuation are followed.
Spelling is correct.
Total: % out of 100%
Points Possible: 20 x % =
Content: 80%
Comments on the assignment will include points off per question.
Were all the questions answered in complete, grammatically correct sentences?
Were answers fully explained?
Was information from the video used in the interpretation of the pictures when the photo was unclear?
Were the appropriate concepts used in the answers?
Was it clear that the author understood the concepts?
Were words spelled correctly?
Application of concepts from the text: 20%
Were nonverbal communication codes from the text referenced in the appropriate questions?
· Body movement & posture
· Emblems
· Illustrators
· Affect displays
· Regulators
· Eye contact
· Facial expression
· Vocal cues
· Personal space
· Territory
· Touch
· Appearance
Were nonverbal skills & strategies from the text referenced in the appropriate questions?
· Consider nonverbal cues in context
· Look for clusters of nonverbal cues
· Consider past experience when interpreting nonverbal cues
· Check your perception with others
Were cultural barriers from the text referenced in the appropriate questions?
· Ethnocentrism
· Different communication codes
· Stereotyping & prejudice
· Assuming similarities
· Assuming differences
· Sex & gender
· Sexual orientation
· Race & Ethnicity
· Age
· Social class
Points Possible: 50 points x % =
Nonverbal Communication Codes
BSCOM/234 Version 1
5
University of Phoenix Material
Nonverbal Communication Codes
1. What nonverbal messages are being sent in this image?
2. What type of nonverbal communication codes are being used to deliver the messages?
3. What effect does each message have on the other people in the image?
4. What nonverbal communication skills and strategies could be used to communicate effectively in this situation?
1. What cultural barriers are seen in this image?
2. What type of nonverbal communication codes are being used to deliver the messages?
3. What effect does each message have on the other people in the image?
4. What nonverbal communication skills and strategies could be used to communicate effectively in this situation?
1. What nonverbal mess.
After developing the lessons and the project, I have comfort in the ability to:
>Recognize complex data-type to discover what analyses are likely.
>Determine measures of center and spread to explain quantitative data.
>Use a mixture of spreadsheet functionality to obtain penetrations from data.
>Build charts and graphs to describe the results of our analysis
>Will be comfortable posing problems that can be answered with a given dataset and then answering those subjects
>Analyze a prospective dataset using Excel
An Empirical Study on Comment Classificationijtsrd
Due to increasing technologies in the interactive web applications, there has been a lot of development in E commerce and online social networking activities. The comments or the post always plays a vital role in understanding of the attitude towards a particular topic, product of the online users. Most of the times these comments or posts help the other users to understand the scenario and to take the right decision on the web platform. Machine learning plays a vital role to understand and to estimate the accurate semantics of these posts and comments. Natural language processing is widely used for this, Most of the times natural language processing does not yield much expected results in the classification of these comments due to the complexity in the narration. These complexities generally arise either due to poor narration of the comments or highly sarcastic contents in the comments. So to overcome these problems this paper broadly studies all the past work on comment classification and try to find the new way of machine learning to get the highly classified labels of the comments. Shubham Derhgawen | Rajesh Tak | Subhasish Chatterjee "An Empirical Study on Comment Classification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28053.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/28053/an-empirical-study-on-comment-classification/shubham-derhgawen
Identification of monolingual and code-switch information from English-Kannad...IJECEIAES
Code-switching is a very common occurrence in social media communication, predominantly found in multilingual countries like India. Using more than one language in communication is known as codeswitching or code-mixing. Some of the important applications of codeswitch are machine translation (MT), shallow parsing, dialog systems, and semantic parsing. Identifying code-switch and monolingual information is useful for better communication in online networking websites. In this paper, we performed a character level n-gram approach to identify monolingual and code-switch information from English-Kannada social media data. We paralleled various machine learning techniques such as naïve Bayes (NB), support vector classifier (SVC), logistic regression (LR) and neural network (NN) on English-Kannada code-switch (EKCS) data. From the proposed approach, it is observed that the character level n-gram approach provides 1.8% to 4.1% of improvement in terms of Accuracy and 1.6% to 3.8% of improvement in F1-score. Also observed that SVC and NN techniques are outperformed in terms of accuracy (97.9%) and F1-score (98%) with character level n-gram.
Content out of 70MetCommentsCreate a short Microsoft® .docxmaxinesmith73660
Content: % out of 70%
Met?
Comments
Create a short Microsoft® PowerPoint® presentation or video that includes the following:
· personal background of the person interviewed (10%)
· where the person have lived (10%)
· any intersting cultural facts in the person’s history (15%)
· any experiences this person had adapting to new cultures (15%)
· a comparison of your cultural experiences with those of the individual interviewed (20%)
Style: % out of 10%
Did your slides utilize white space and avoid having too dense text?
Were your slides designed to be visually pleasing?
Mechanics: % out of 20%
Did you include speaker’s notes in your PowerPoint? They should be the majority of your presentation
Rules of grammar, usage, and punctuation are followed.
Spelling is correct.
Total: % out of 100%
Points Possible: 20 x % =
Content: 80%
Comments on the assignment will include points off per question.
Were all the questions answered in complete, grammatically correct sentences?
Were answers fully explained?
Was information from the video used in the interpretation of the pictures when the photo was unclear?
Were the appropriate concepts used in the answers?
Was it clear that the author understood the concepts?
Were words spelled correctly?
Application of concepts from the text: 20%
Were nonverbal communication codes from the text referenced in the appropriate questions?
· Body movement & posture
· Emblems
· Illustrators
· Affect displays
· Regulators
· Eye contact
· Facial expression
· Vocal cues
· Personal space
· Territory
· Touch
· Appearance
Were nonverbal skills & strategies from the text referenced in the appropriate questions?
· Consider nonverbal cues in context
· Look for clusters of nonverbal cues
· Consider past experience when interpreting nonverbal cues
· Check your perception with others
Were cultural barriers from the text referenced in the appropriate questions?
· Ethnocentrism
· Different communication codes
· Stereotyping & prejudice
· Assuming similarities
· Assuming differences
· Sex & gender
· Sexual orientation
· Race & Ethnicity
· Age
· Social class
Points Possible: 50 points x % =
Nonverbal Communication Codes
BSCOM/234 Version 1
5
University of Phoenix Material
Nonverbal Communication Codes
1. What nonverbal messages are being sent in this image?
2. What type of nonverbal communication codes are being used to deliver the messages?
3. What effect does each message have on the other people in the image?
4. What nonverbal communication skills and strategies could be used to communicate effectively in this situation?
1. What cultural barriers are seen in this image?
2. What type of nonverbal communication codes are being used to deliver the messages?
3. What effect does each message have on the other people in the image?
4. What nonverbal communication skills and strategies could be used to communicate effectively in this situation?
1. What nonverbal mess.
After developing the lessons and the project, I have comfort in the ability to:
>Recognize complex data-type to discover what analyses are likely.
>Determine measures of center and spread to explain quantitative data.
>Use a mixture of spreadsheet functionality to obtain penetrations from data.
>Build charts and graphs to describe the results of our analysis
>Will be comfortable posing problems that can be answered with a given dataset and then answering those subjects
>Analyze a prospective dataset using Excel
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
1. Good afternoon everyone. I am…..and this is my … semester. Today I
will give a presentation on Code-switching in virtual communication
in Bangladesh.
Code switching
In Sociolinguistics, code refers to a language. Code-
switching means switching from one particular language to
another within a sentence. It is also known as Code mixing.
Various types of code-switching occur within a sentence.
Situational Code-switching:
Intra-Sentential Code-switching:
Metaphorical Code-switching:
Purpose of the Research:
2. To explore patterns of code-switching in virtual
communication among people in Bangladesh and the findings
presented here are mainly based on Google forms surveys
conducted within 21 participants.
Analysis:
1)According to the research, 52.4 % of students switch codes
more than 5-10 times per day, 28.6 % switch codes 10 -15
times per day, and the rest switch codes fewer than 15 times
per day.
2) 81 % believe code-switching is beneficial for
communication, 14.3 percent said its beneficial for
proficiency and rest said for accuracy.
3)23.8 % say they practice code-switching in the classroom
and home. 81 percent said they do this in social media and
rest 4.8 percent code switch for face-to-face conversation and
others.
4)57.1 % agree that code switching will become the new
standard mode of communication, 14.3 percent strongly
agree and others disagree
3. 5)52.4 % stick to no for grammatical rules, 28.6 percent said
yes and 19 percent said sometimes they use grammatical
rules
Last qus,
6)57.1% said yes that they think code-switching can help us
to save our time, 38.1 percent said maybe and rest said no.
My personal observation is that, Code-switching has become
the new form of communication mostly orally among the
new generation. Most people, do code-switching
unconsciously without even knowing it. But the most
important challenge is to give this trend a proper direction.
People must pick a certain code anytime they talk, and they
can move from one code to another or mix codes even within
brief utterances.
4. code-switching has emerged as a new style of communication,
primarily oral, among the younger generation. Most people
swap codes instinctively and without even realizing it.