Video Transcripts Research Articles

Generación de Vínculos Relacionados a Textos Transcritos para Videos de YouTube

The way people learn has undergone a significant transformation thanks to the advancement of technology. Various digital tools complement daily and academic activities, facilitating access to updated and diverse information. The Internet, in particular, has positioned itself as the primary source of information, offering a large amount of textual and audiovisual content, with short content in the form of videos being the most popular. However, the learning process inevitably involves acquiring new concepts and terms. When encountering unfamiliar vocabulary in videos, people often search for additional information to understand the content better. Therefore, this research seeks to develop a tool capable of analyzing video transcripts using Natural Language Processing techniques to identify key terms and relate them to other relevant information sources, thus facilitating learning. When evaluating the relevance of terms to the textual content of videos on various topics using an Artificial Intelligence model, a relevance greater than 75% was evidenced for all terms. This confirms the efficacy of this approach for analyzing and understanding the textual content of transcribed videos.

Captioning for Clarity: Mastering Stress with Word-Based vs. Phonetic Video Transcriptions

This study explores an understudied aspect of video captioning in language learning: the use of phonetic transcription. While extensive research has examined the effects of traditional word-based captioning, the potential benefits of phonetic transcription captions remain largely unexplored. To address this knowledge gap, a quasi-experimental study was conducted comparing two captioning conditions: traditional word-based captions and phonetic transcription captions. Two groups of English as a Foreign Language (EFL) learners were purposively selected based on their course enrollment, with participants volunteering for the study. The control group viewed videos with standard word captions, while the experimental group watched videos captioned with phonetic transcriptions. Pre- and post-tests were administered to assess improvements in word stress pronunciation. The results revealed no statistically significant difference between the post-test scores of the control and experimental groups. This suggests that both captioning methods - words and phonetic transcription - positively impact stress pronunciation learning. The findings indicate that enhanced stress pronunciation may contribute to overall language intelligibility and fluency, potentially leading to improved language learning outcomes. This study opens avenues for future research on the application of phonetic transcription in other areas of pronunciation, such as intonation and connected speech.

Analysis On Code-Switching Encountered in The Conversation of Daniel Mananta and His Guest Stars on “Daniel Tetangga Kamu” Video Youtube Channel

This study aims to describe the type of code-switching encountered in the conversation of Daniel Mananta and his guest stars on “Daniel Tetangga Kamu” video Youtube channel. This research covered three types of code-switching as a discussion for further linguistic study on code-switching. A descriptive qualitative method is used for this study to analyze the data collected from three videos out of the videos uploaded of Daniel Mananta in youtube. The method is applied to give a clear description of the data according to the three types of code-switching by Poplack. Then, the data were sorted out of the selected corpora from video transcription. The result of this analysis showed that there were types of code-switching found in this conversation, including inter-sentential switching, intra-sentential switching, and tag switching. Type of code-switching which is intra-sentential was the most frequently encountered in corpora with 111 data.

“Stay tuned”: an exploratory content and thematic analysis of brain injury videos on YouTube

Purpose This exploratory study aimed to examine brain injury videos on YouTube to determine who posted about brain injury, content categories of videos, and how brain injury was represented. Methods A mixed methods approach was used. Brain injury videos on YouTube were collected in November 2022 and analysed quantitatively and qualitatively using descriptive statistics and content analysis. Visual data analysis was used to generate visual descriptions of a representative sample of the videos, and these were thematically analysed alongside the video transcripts. Results The sample of 100 YouTube videos consisted of educational, lived experience, and promotional videos. Medical organisations and hospitals were the predominant source of videos. An overarching theme of “Video tells a story” was generated from eighteen visual descriptions and transcripts which contained three major themes: (a) we choose how the story is told, (b) recovery is a process, and (c) it changed my life. Conclusion YouTube may have a storytelling role for both people with a brain injury wishing to share their story and for health professionals wishing to communicate information about brain injury. This research may have clinical implications for the integration of YouTube in brain injury rehabilitation and the use of YouTube for health communication.

Building a searchable online corpus of Australian and New Zealand aligned speech

ABSTRACT Advances in automatic speech recognition technology, increases in bandwidth availability, and the widespread use of video streaming and sharing platforms have opened new horizons for corpus phonetics. CoANZSE Audio, a searchable online version of the Corpus of Australian and New Zealand Spoken English, provides access to over 195 million words of transcribed speech from transcripts of videos uploaded to YouTube by councils and other local government entities in Australia and New Zealand. Audio and forced alignment files are also available, making the resource suitable for the investigation of a range of research questions pertaining to morphosyntax, phonetics, and discourse. The resource, which is freely available via login through CLARIN, Europe’s main language resources infrastructure network, was created through the use of open-source tools and software: yt-dlp, a Python library for collecting data from video and streaming websites; the Montreal Forced Aligner, a recent neural network alignment suite; and Parselmouth-Praat, Python bindings for the Praat acoustic analysis software. The website is powered by BlackLab, which combines a powerful search engine based on Apache Lucene with an intuitive web frontend. CoANZSE Audio may be useful for the investigation of regional differentiation of language features, and with additional annotation, differences in feature use according to social or demographic groups. Recent applications have included studies of double modals, a rare syntactic feature, and apology sequences. The nature of the audio and alignment data may make the resource especially suitable for the study of regional phonetic variation. Furthermore, the methods used to create the resource may be of interest to researchers seeking to adopt a pipeline approach for the creation of specialized corpora from publicly available online content.

Sistem Appraisal dalam Video Kritik terhadap Kebijakan Pemerintah Daerah

Social media has become an important means for people to express their opinions and criticisms on various issues, including issues related to local government policies. Criticism towards local governments triggers various interpretations in society. Academics in the field of linguistics should respond to such issues by conducting research, one of which is discourse analysis from the perspective of Systemic Functional Linguistics. The purpose of this research is to reveal how speakers express their attitudes, judgments, and emotions through the language they use to convey criticism towards local government policies. This research employs a qualitative design. The data source is derived from the social media platform, TikTok in the form of videos criticizing local government policies. The result of this research indicate that the aspect of judgment dominates in the transcripts of videos criticizing local government policies followed by appreciation in second place and affect in third place. The most frequently used judgment is personal – negative – criticizing – direct. This aligns with the main objective of the videos criticizing local government policies used as data in this research, which is to criticize or evaluate. After judgment, negative appreciation is the second most prevalent. Lastly, negative affect – direct is the least frequently found in the research data.

Video Transcription in to Enhanced Text Summarization

Video Transcription in to Enhanced Text Summarization

Variasi Morfologis Bahasa Slang dalam Transkrip Podcast

This research aims to: (a) to describe the morphological variations of the slang lexicon in podcast transcripts, and (b) to explain the process of forming these morphological variations. The research methodology used is descriptive in nature. Qualitative data obtained from the research is described based on the research objectives. The data sources for this research are the YouTube accounts of Volix media, HAS Creative, and Slap Show. The data collection technique involves several stages: (1) opening the YouTube social media application, (2) reviewing video transcripts from the Volix, HAS Creative, and Slap Show YouTube channels, (3) identifying data in the form of various slang terms found in the video transcripts, (4) documenting the data in a notebook. The data analysis technique consists of four stages: (1) identifying the collected data, (2) classifying the data based on the research objectives using a predefined format, (3) analyzing the classified data, and (4) formulating conclusions based on the analysis results. The research findings show that the slang lexicon used in the podcast transcripts can be categorized into two forms: (a) monomorphemic (68 instances), such as okay, spontaneous, shy, and ego, and (b) polymorphemic (57 instances), such as rupiah slave, baperan, and prepare. The formation of the slang lexicon in podcast transcripts involves several processes: (a) affixation (15 instances), such as complaining, ignya, and teasing, (b) reduplication (10 instances), such as guessing, carelessly, and saying goodbye, (c) composition (2 instances), such as rupiah slaves and hourly average, and (d) acronymization (18 instances), such as AC, VPN, and KTP.

Transcript Summarizer For YouTube

The YouTube Transcript Summarizer is a web application. The application provides users with a simple interface to summarize the transcript of a YouTube video. Users can paste a YouTube video link into the application, which then extracts the video's transcript and generates a concise summary. The summary includes key points from the video, enabling users to quickly grasp the content without watching the entire video. This project aims to improve the efficiency of consuming YouTube video content by providing users with a convenient summarization tool. The system is integrated with existing YouTube interfaces, making it user-friendly and accessible to a wide range of users. Overall, the YouTube Transcript Summarizer aims to save time, improve comprehension, increase accessibility, and facilitate research for YouTube content consumers. The YouTube Transcript Summarizer is poised to make YouTube content more accessible, saving users time and providing an effective way to quickly evaluate the content of videos before investing their time in watching them. This tool can be a game-changer for content creators, researchers, students, and anyone seeking to extract valuable information from the vast YouTube library Keywords: Summarization, Efficiency, Time Saving, Accessibility, User-Friendly, Information Extraction

GlobalLingua: Empowering Multilingual Access to YouTube Video Transcripts with Automated Translation

GlobalLingua removes language barriers that block online video content worldwide. This application lets content creators, educators, and individuals obtain and translate YouTube transcripts. The software uses clever technology to simplify user-provided YouTube video URLs. PyTube quickly gets videos, titles, and transcripts using the YouTube_transcript_api. The software also easily converts English texts into the user-specified language with the Google Convert API. It powerfully removes temporary files and processes movies to increase speed and reliability. Automatic YouTube video transcript translation software increases global content accessibility, knowledge exchange, and cross-cultural communication. The application automates transcript extraction and translation, enabling multilingual content and digital inclusion

Video Transcripts Summarization using OpenAI Whisper and GPT Model

Abstract: In today’s digital age, a vast amount of video content is generated and shared on the internet every minute. However, extracting relevant information from these videos can be time-consuming and challenging. This is where video transcript summarization comes in, providing a concise summary of video content without the need to watch the entire video. The video transcript summarization system aims to streamline the process of extracting key insights and information from video content by generating concise and informative summaries from their transcripts. In the dynamic landscape of video content, existing approaches to transcript summarization have encountered challenges that limit their effectiveness. Issues such as compromised accuracy, prolonged processing times and a restricted focus on YouTube's captioned videos have prompted the exploration of alternative solutions. This paper introduces a novel approach that tackles these limitations head-on, employing innovative technologies to redefine the landscape of video transcript summarization. To address the identified limitations, we propose an alternative strategy that hinges on the utilization of advanced technologies like OpenAI Whisper Model Automatic Speech Recognition(ASR) for video’s Transcription and Generative Pre-trained Transformer (GPT) model for Summarization. Through the integration of the OpenAI Whisper model for transcription and GPT models for summarization, our proposed approach strives to redefine standards in accuracy, processing efficiency, multilingual support, and exhibit the capability to generate either extractive or abstractive summaries. In the context of natural language processing (NLP) and text summarization ROUGE (Recall-Oriented Understudy for Gisting Evaluation) metrics will be used to evaluate the quality of generated summaries compared to human referenced summaries

Summarization of Video using Audio

Abstract: Online education has emerged as a highly effective means of delivering quality education to students. Its popularity has increased due to the high-quality visual and graphical content, delivered by subject matter experts, and the convenience of learning anytime and anywhere. However, students may face time constraints that prevent them from fully engaging with the course content. To address this issue, video transcript summarizers have gained popularity. These tools extract the most important topics from a video, allowing students to understand the essence of the class without having to watch the entire video. Our system focuses on developing a module using txtai.pipeline with Python to summarize online class videos. We use Whisper, a general-purpose speech recognition model, to train our model on a large dataset of diverse audio. The model takes the URL of a video as input and uses two algorithms to summarize the content: TF-IDF and Gensim. The summarization process is subjective, and we have incorporated two prominent methods: cosine similarity and ROUGE score. The former does not require a human-generated summary for reference, while the latter does. Our results show that the efficiency obtained using cosine similarity is greater than 90% in both TF-IDF and Gensim cases. The efficiency obtained in the case of ROUGE score is between 40-50%.

A survey on audio analysis: Text characterization and summarization

The integration of cutting-edge natural language processing (NLP) technology for smooth audio-to-text conversion and summarization is examined in this survey. Utilizing Facebook’s BART model for succinct summaries and Google’s Speech-to-Text API for precise transcription. The report highlights the value of sophisticated summarization models and precise transcription. It talks about how the system can be used in a variety of fields, such as podcast and video transcript generation, automated meeting transcription and summarization, content indexing and search, and more. In addition to addressing issues like context preservation and bias reduction, the survey assesses relevant research on text generation, LSTM networks, and summarization techniques. Overall, by incorporating state-of-the-art technology, this study advances the processing of audio content and eventually makes it easier to extract valuable information.

Assessing Patients Perception: Analyzing the Quality, Reliability, Comprehensibility, and the Mentioned Medical Concepts of Traumatic Brain Injury Videos on YouTube

AimThe aim of this study is to analyze the quality, reliability, comprehensibility, and the mentioned medical concepts of traumatic brain injury (TBI) related videos on YouTube. Material – Methods"Traumatic brain injury" and related Google Trends queries were used and 328 videos included. Categorization, quality assessment via a 5-point Global Quality Scale, reliability evaluation using a modified DISCERN scale, comprehensibility assessment using Flesch-Kincaid Reading Ease and Flesch-Kincaid Grade Level, and consensus-based classification for usefulness were performed. Target audience categorization was content-based. Text mining techniques were used to identify biomedical terms in video transcripts. ResultsMost of the videos were intended for non-healthcare professionals and deemed useful. The videos had intermediate quality and moderate level of reliability. The comprehensibility of the videos exceeded the recommended levels. Videos predominantly covered TBI symptoms, the severity of the condition, its impact on individuals, and possibly strategies related to diagnosis and treatment. ConclusionsResults suggest the requirement for higher quality and reliability in YouTube content about TBI. Emphasis should be placed on clear and accurate language to promote comprehensibility. Continued research, guidelines, education, and platform oversight can enhance the spread of reliable health information on social media, benefiting creators and consumers in this field.

Teacher’s Talk in English Classroom Using Foreign Language Interaction (FLINT) System

The researcher conducted the research to describe the teacher and student interaction during the teaching-learning process and to analyze the frequent FLINT categories by Moskowitz (1976). The participant in this research was an English female teacher taught in class VII F at SMP Negeri 1 Sungai Raya in the academic year 2022/2023. This research was a case study design that used qualitative method. The data was collected by observing the teacher and student interaction during the teaching-learning process. The researcher used the teacher talk video transcript in analyzing the FLINT categories. The result of the research showed that the teacher’s dominant language was Bahasa Indonesia. The teacher’s utterances in Bahasa Indonesia appeared 95 times during the teaching-learning process, which means the teacher used Bahasa Indonesia in English lessons. The teacher should be built good oral during the teaching-learning process, not only focus on delivering the material. The frequent categories used by the teacher were giving information and asking questions. Moreover, the rare category the teacher used was the student’s ideas. Through analyzing the FLINT system, teacher talk in the classroom was accessible in describing the dominant language performed by the teacher and analyzed frequent categories used by the teacher during the teaching-learning process.

Exploring teacher talk in training classrooms: A case study at SD Linimasa, Kuningan

The aim of this study is to investigate the types of teacher talk and their meanings in dealing with diverse students. This research aimed to explore several fundamental aspects that occurred in classroom interaction. They are: 1) the types of teacher talk; 2) the most dominant and least performed type of teacher talk; and 3) the contribution of teacher talk to supporting learning. This research was a case study with the participation of three English teachers. The data had been collected through classroom observation, semi-structured interviews, and questionnaires. In examining the utterances uttered by all teachers, video recordings were utilised throughout the learning process. The result of the video transcription was then analysed using Moskowitz’s FLINT system to categorise the type of teacher talk. The result was then cross-checked with the interview and questionnaire to support the validity of the data. The study's findings demonstrated that during the teaching and learning process, teachers used nearly every kind of teacher discourse. Joking was the least frequent sort of speech, while asking questions was the most frequent. Through their utterances during the session, the teacher also provided support to the students who transferred from situations where English was not their first or second language. Teachers facing comparable situations may find it helpful to consider the study's implications and outcomes while trying to boost student engagement, which in turn encourages students to participate more actively in the learning process. Keywords: Exploration; classroom interaction; teachers’ talk;

An exploratory study of social presence and cognitive engagement association in a collaborative virtual reality learning environment

As the utilization of virtual reality (VR) in engineering education increases, researchers are increasingly focused on enhancing teaching and learning within VR environments. Cognitive engagement among the participants is a fundamental outcome in any learning environment, where social interaction often plays a pivotal role. This study contributes to VR teaching and learning research by investigating the association between social presence indicators and modes of cognitive engagement in a desktop collaborative virtual reality (VR) learning environment based on the social presence theory and the cognitive engagement definition of the Interactive-Constructive-Active-Passive framework. The study participants logged into the VR platform to collaboratively solve simulated engineering statics problems. The transcripts of students' interaction videos were coded based on codebooks for both social presence and cognitive engagement. The study revealed that social presence indicators are significantly associated with the three modes of cognitive engagement (active, constructive, and interactive). Additionally, interactive open communication emerged as the primary social presence element utilized by students during cognitive engagement with peers in the learning environment. This study's findings have implications for research and practice in enhancing students' cognitive engagement through their social interactions within VR learning environment.

Codeswitching from Indonesian to English Encountered in the Three Naila Farhana's YouTube Videos

This study aims at describing the types and functions of codeswitching encountered in Naila Fahana’s YouTube videos. The data were collected from Naila Farhana YouTube channel with three selected videos entitled Mau Tips Lancar Belajar Bahasa Inggris, Pelajari 5 Kunci Sukses (Be Fluent in English, learn 5 successful keys), Cara Bahasa Inggris Tanpa Ngeblank (Learn English without Going Blank), American Accent_ Cara Belajar Aksen Amerika (American Accent_ How to Learn American Accent). This research was a descriptive study in which the writer described types of codeswitching using a theory of Peter Stockwell and functions of codeswitching using a theory of Marasigan. In collecting the data, this study utilized human instrument in which the researcher as the main source. Then, the data were sorted out of the corpora from video transcriptions with 4,622 words in total. The findings of this study showed that the dominant type of codeswithing is intrasentential switching (IaSCS) with 102 data out of 123 data and the dominant function of codeswitching is message of qualification (MQ) with 50 data out of 123 data. This research covered three types and seven functions of codeswitching as a discussion for further linguistic study on codeswitching.

AN OFF-RECORD POLITENESS STRATEGY IN COMMISSION III OF THE DPR RI ON PREMEDITATED MURDER OF BRIGADIER J

This paper aims to find out the kind of off-record strategies uttered by the participants in The Hearing Meeting (RDP), with a focus on Brown and Levinson's (1978) theory. This study's data analysis techniques include watching the video, transcribing, translating, categorizing, and classifying the data into a politeness strategy. The researchers are interested on the murder case of Brigadier Novriansyah Yosua Hutabarat or Brigadate J at Inspector General Ferdy Sambo's official residence. The video transcripts from the meeting were analyzed, and the researchers found 10 out of 15 techniques off record politeness strategies uttered by the participants of the hearing meeting and forms of politely.

Towards Designing Choreography Curriculum Template for African Contemporary Dance Using Dayo Liadi’s Olori-Oko Dance Performance

Modern dance techniques such as choreography gives the genre a unique language that can be used to expand the dance technique and dance composition as used by choreographers. Dayo Liadi as a choreographer and study in this article has used contemporary dance genre of body gestures to communicate his message through signs and cultural symbols, towards the appreciation from the audience. However, there are many thematic areas including space, shapes, images, body movement, and other paraphernalia employed in the style called contemporary dance type of choreography. Thus, all of these must be preserved and replicated as unique dance techniques. Therefore, the need to study and propose an indigenous choreography curriculum that emanates from Dayo Liadi’s creative work i.e. Olori Oko performance. The study is anchored on Michael Forkine’s Perspective of Adorno Theodor’s Philosophical Aesthetic theory. This is with the view to incorporate home-grown curriculum contents into dance studies in theatre schools in Nigeria and in Africa. The study adopted quantitative research method, involving participants’ observation, transcription and content analysis of lyrics and video using a checklist to conduct thorough video pre-view and review of the choreographic work. Major findings revealed a need for collaboration and performances to sharpen and widen the horizon of the artistic and creativity appreciation, with the view to incorporate new dance techniques into the Nigerian and African dance techniques such as incorporated in Dayo Liadi’s creative work. The study recommend direct implementation or adoption of the proposed curriculum template as part of choreography dance studies in theatre curriculum among departments in higher institutions Nigeria and Africa.