Transcription Of Text Research Articles

A Comparison of Different Topic Modeling Methods through a Real Case Study of Italian Customer Care

The paper deals with the analysis of conversation transcriptions between customers and agents in a call center of a customer care service. The objective is to support the analysis of text transcription of human-to-human conversations, to obtain reports on customer problems and complaints, and on the way an agent has solved them. The aim is to provide customer care service with a high level of efficiency and user satisfaction. To this aim, topic modeling is considered since it facilitates insightful analysis from large documents and datasets, such as a summarization of the main topics and topic characteristics. This paper presents a performance comparison of four topic modeling algorithms: (i) Latent Dirichlet Allocation (LDA); (ii) Non-negative Matrix Factorization (NMF); (iii) Neural-ProdLDA (Neural LDA) and Contextualized Topic Models (CTM). The comparison study is based on a database containing real conversation transcriptions in Italian Natural Language. Experimental results and different topic evaluation metrics are analyzed in this paper to determine the most suitable model for the case study. The gained knowledge can be exploited by practitioners to identify the optimal strategy and to perform and evaluate topic modeling on Italian natural language transcriptions of human-to-human conversations. This work can be an asset for grounding applications of topic modeling and can be inspiring for similar case studies in the domain of customer care quality.

Seeing you reminds me of things that never happened: Attachment anxiety predicts false memories when people can see the communicator.

Previous research suggests that attachment avoidance is robustly linked to memory errors of omission-such as forgetting information or events that have occurred. Moreover, these avoidance-related errors of omission are the strongest for relational stimuli (e.g., avoidant people have trouble remembering relationship-related words, but not neutral ones). Conversely, an emerging body of studies has linked attachment anxiety to memory errors of commission-such as falsely remembering events that never actually happened. The present article describes three studies (Ns = 204, 651, 547) that replicate the correlation between attachment anxiety and false memories. Moreover, the present studies experimentally explored the boundary conditions under which anxiety might predict false memories. Results indicated that attachment anxiety predicts false memories only when participants could see a video of another person conveying information-but not when reading a text transcript of the same information or when listening to the audio only. This is consistent with prior studies which suggest that highly attachment-anxious individuals are hypervigilant to others' emotional expressions and may use them to make incorrect inferences (which potentially become falsely encoded into memory). (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Exploring the possibilities of Thomson’s fourth paradigm transformation—The case for a multimodal approach to digital oral history?

Abstract This article seeks to reorientate ‘digital oral history’ towards a new research paradigm, Multimodal Digital Oral History (MDOH), and in so doing it seeks to build upon Alistair Thomson’s (Thomson, A., 2007, Four paradigm transformations in oral history. Oral History Review, 34(1): 49–70.) characterization of a ‘dizzying digital revolution’ and paradigmatic transformation in oral history (OH). Calling for a recalibration of the current dominance of the textual transcript, and for active engagement with the oral, aural, and sonic affordances of both retro-digitized and born digital OH (DOH) collections, we call for a re-orientation of the digital from passive to generative and self-reflexive in the human–machine study of spoken word recordings. First, we take stock of the field of DOH as it is currently conceived and the ways in which it has or has not answered calls for a return to the orality of the interview by digital means. Secondly, we address the predominant trend of working with transcriptions in digital analysis of spoken word recordings and the tools being used by oral historians. Thirdly, we ask about the emerging possibilities—tools and experimental methodologies—for sonic analysis of spoken word collections within and beyond OH, looking to intersections with digital humanities, sociolinguistics, and sound studies. Lastly, we consider ethical questions and practicalities concomitant with data-driven methods, analyses and technologies like AI for the study of sonic research artefacts, reflections that dovetail with digital hermeneutics and digital tool criticism and point towards a new MDOH departure, a sub-field that has potential to inform the many fields that seek patterns in audio, audio-visual, and post-textual materials, serially and at scale.

Txt2Vid: Ultra-Low Bitrate Compression of Talking-Head Videos via Text

Video represents the majority of internet traffic today, driving a continual race between the generation of higher quality content, transmission of larger file sizes, and the development of network infrastructure. In addition, the recent COVID-19 pandemic fueled a surge in the use of video conferencing tools. Since videos take up considerable bandwidth ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 100$ </tex-math></inline-formula> Kbps to a few Mbps), improved video compression can have a substantial impact on network performance for live and pre-recorded content, providing broader access to multimedia content worldwide. We present a novel video compression pipeline, called Txt2Vid, which dramatically reduces data transmission rates by compressing webcam videos (“talking-head videos”) to a text transcript. The text is transmitted and decoded into a realistic reconstruction of the original video using recent advances in deep learning based voice cloning and lip syncing models. Our generative pipeline achieves two to three orders of magnitude reduction in the bitrate as compared to the standard audio-video codecs (encoders-decoders), while maintaining equivalent Quality-of-Experience based on a subjective evaluation by users ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n=242$ </tex-math></inline-formula> ) in an online study. The Txt2Vid framework opens up the potential for creating novel applications such as enabling audio-video communication during poor internet connectivity, or in remote terrains with limited bandwidth. The code for this work is available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/tpulkit/txt2vid.git</uri> .

Physician Note Composition Patterns and Time on the EHR Across Specialty Types: a National, Cross-sectional Study.

The burden of clinical documentation in electronic health records (EHRs) has been associated with physician burnout. Numerous tools (e.g., note templates and dictation services) exist to ease documentation burden, but little evidence exists regarding how physicians use these tools in combination and the degree to which these strategies correlate with reduced time spent on documentation. To characterize EHR note composition strategies, how these strategies differ in time spent on notes and the EHR, and their distribution across specialty types. Secondary analysis of physician-level measures of note composition and EHR use derived from Epic Systems' Signal data warehouse. We used k-means clustering to identify documentation strategies, and ordinary least squares regression to analyze the relationship between documentation strategies and physician time spent in the EHR, on notes, and outside scheduled hours. A total of 215,207 US-based ambulatory physicians using the Epic EHR between September 2020 and May 2021. Percent of note text derived from each of five documentation tools: SmartTools, copy/paste, manual text, NoteWriter, and voice recognition and transcription; average total and after-hours EHR time per visit; average time on notes per visit. Six distinct note composition strategies emerged in cluster analyses. The most common strategy was predominant SmartTools use (n=89,718). In adjusted analyses, physicians using primarily transcription and dictation (n=15,928) spent less time on notes than physicians with predominant Smart Tool use. (b=-1.30, 95% CI=-1.62, -0.99, p<0.001; average 4.8 min per visit), while those using mostly copy/paste (n=23,426) spent more time on notes (b=2.38, 95% CI=1.92, 2.84, p<0.001; average 13.1 min per visit). Physicians' note composition strategies have implications for both time in notes and after-hours EHR use, suggesting that how physicians use EHR-based documentation tools can be a key lever for institutions investing in EHR tools and training to reduce documentation time and alleviate EHR-associated burden.

Application of Fischer semi discriminant analysis for speaker diarization in costa rican radio broadcasts

Automatic segmentation and classification of audio streams is a challenging problem, with many applications, such as indexing multi – media digital libraries, information retrieving, and the building of speech corpus or spoken corpus) for particular languages and accents. Those corpus is a database of speech audio files and the corresponding text transcriptions. Among the several steps and tasks required for any of those applications, the speaker diarization is one of the most relevant, because it pretends to find boundaries in the audio recordings according to who speaks in each fragment. Speaker diarization can be performed in a supervised or unsupervised way and is commonly applied in audios consisting of pure speech. In this work, a first annotated dataset and analysis of speaker diarization for Costa Rican radio broadcasting is performed, using two approaches: a classic one based on k-means clustering, and the more recent Fischer Semi Discriminant. We chose publicly available radio broadcast and decided to compare those systems’ applicability in the complete audio files, which also contains some segments of music and challenging acoustic conditions. Results show a dependency on the results according to the number of speakers in each broadcast, especially in the average cluster purity. The results also show the necessity of further exploration and combining with other classification and segmentation algorithms to better extract useful information from the dataset and allow further development of speech corpus.

The Digital Dickens Notes Project

The Digital Dickens Notes Project

Gaze-assisted automatic captioning of fetal ultrasound videos using three-way multi-modal deep neural networks.

In this work, we present a novel gaze-assisted natural language processing (NLP)-based video captioning model to describe routine second-trimester fetal ultrasound scan videos in a vocabulary of spoken sonography. The primary novelty of our multi-modal approach is that the learned video captioning model is built using a combination of ultrasound video, tracked gaze and textual transcriptions from speech recordings. The textual captions that describe the spatio-temporal scan video content are learnt from sonographer speech recordings. The generation of captions is assisted by sonographer gaze-tracking information reflecting their visual attention while performing live-imaging and interpreting a frozen image. To evaluate the effect of adding, or withholding, different forms of gaze on the video model, we compare spatio-temporal deep networks trained using three multi-modal configurations, namely: (1) a gaze-less neural network with only text and video as input, (2) a neural network additionally using real sonographer gaze in the form of attention maps, and (3) a neural network using automatically-predicted gaze in the form of saliency maps instead. We assess algorithm performance through established general text-based metrics (BLEU, ROUGE-L, F1 score), a domain-specific metric (ARS), and metrics that consider the richness and efficiency of the generated captions with respect to the scan video. Results show that the proposed gaze-assisted models can generate richer and more diverse captions for clinical fetal ultrasound scan videos than those without gaze at the expense of the perceived sentence structure. The results also show that the generated captions are similar to sonographer speech in terms of discussing the visual content and the scanning actions performed.

Applying a cancer model to the generation of writing for performance: Finding (creative) life in death

This paper outlines the creative experiment that led to the composition of Self Portrait / In Cross-Sections / With Bird, writing designed for theatrical performance. The paper sets this experiment within a critical framework that theorises a textual system. The textual system utilises the organismic dynamics of systems biology to delineate the dwelling within and shaping of imaginative spaces that results from the act of writing. Using practice-based research, the experiment seeks to investigate how biological processes might be used to generate innovations in dramatic form by analysing the implementation of one distinct biological process – the generation and proliferation of cancer. Specifically, by applying a model of composition derived from cancer biology to Shakespeare’s Hamlet, it is theorised that a dramaturgy essentially cancerous in nature might emerge. A cancerous mode of composition is realised through the transcription or copying of a foundational Hamlet text, a process which models DNA replication and which allows for a proliferation of mutation errors. The rapid and unchecked accumulation of transcription errors simulates the destructive energy of cancer, embodying the tension between chaos and order by which cancer is characterised. What emerges from the experiment are insights into the relationship between (creative) life and death within a cancerous mode of creative composition. By extrapolating from cancer to biological processes more broadly, the paper argues that a biological mode of composition – one which is alert to the inherent energy of the textual system – can enhance our understanding of the mutual emergence of character, author and text.

Kwént tě tǒp xbì gǎn. Un relato de dos almas que andaban penando

this article presents a short text in di'zhke', or coatec Zapotec, in which the narrator, a participant in the Project for the documentation of the languages of Meso-america (pdLma), relates an experience from his childhood in which his family heard two ghosts one night. as part of the pdLma, a practical orthography for writing di'zhke' was established and preliminary grammatical analyses were devel-oped through text transcription as well as lexical and morphological elicitation. in the introduction to the text, updates to the orthography and linguistic analyses are provided, which are applied to the transcription of the text itself. this text, besides illustrating the grammar of the language, offers an example of how speakers of di’zhke’ conceive of and refer to the dead.

Intensive care nurses' lived experience of altruism and sacrifices during the Covid-19 pandemic: A phenomenological study.

The aim of this study was to understand the lived experience of altruism and sacrifices among Swedish nurses working in intensive care units (ICU) during the COVID-19 pandemic. This was a descriptive phenomenological study. The study was conducted between June 2020 and March 2021 and included 20 nurses who were directly involved in the ICU care of COVID-19 patients in Sweden during the pandemic. The text transcripts were analysed using Malterud's Systematic Text Condensation. The analysis revealed four themes. The work situation changed from 1 day to another-the nurses were brutally confronted with a new and highly demanding situation. Adapting to the chaotic situation-despite fear, anguish and exhaustion, the nurses adapted to the new premises. They shouldered the moral responsibility and responded to the needs of the patients and the health care system since they had the competence. Being confronted with ethical and moral challenges-the nurses were overwhelmed by feelings of helplessness and inadequacy because despite how hard they worked, they were still unable to provide care with dignity and of acceptable quality. The importance of supporting each other-collegiality was fundamental to the nurses' ability to cope with the situation. Taken together, being exposed to a constantly changing situation, facing the anguish and misery of patients, families, and colleagues, and being confronted with a conflict between the moral obligation to provide care of high quality and the possibility to fulfil this commitment resulted in suffering among the nurses. Collegial back-up and a supportive culture within the caring team were important for the nurses' endurance. The study contributes an understanding of nurses' lived experience of working during the COVID-19 pandemic and highlights the importance of protecting and preparing nurses and nursing organisation for potential future crises.

Accessibility, Usability, Inclusivity: Information Standards, Guidelines, &amp; Best Practices Sponsored by the ASIS&amp;T Standards Committee

AbstractThis panel, sponsored by the ASIS&amp;T Standards Committee, will explore how information standards, guidelines, best practices, and efforts for increasing the accessibility and usability of information resources can contribute to an information‐resilient society. It will start with by addressing several new standard efforts for web accessibility in the data‐driven age led by the W3, including mobile accessibility, cognitive accessibility, and inaccessibility examinations. A special report will then be given by the leader of an IMLS‐funded project on the newly published Digital Library Accessibility and Usability Guidelines that support blind and visually impaired users who rely on screen readers to interact with digital libraries. A case study on Video/Audio to Text to Tagging will be presented, revealing the best practices on translating audio files to time stamped text transcripts for indexing, classifying, and enriching the original content. A final open discussion on “inclusivity” will involve the audience, to highlight the needs, challenges, and standards for enabling inclusivity and ensuring that everyone who faces accessibility barriers due to disability, literacy, digital literacy, or aging, can access, use, and participate in the Internet and all its information.

INCONSISTENCIES IN TRANSCRIPTION AND TRANSLATION OF TEXTS OF ANCIENT TURKIC WRITTEN MONUMENTS

The article discusses in detail the issues of discrepancies in transcription and translations of texts of ancient Turkic written monuments. It is indicated that in ancient Turkic written texts and their translations, a method of transcription is used that reflects a clear image of the sound composition of words. In the history of the development of writing, especially the reconstruction and restoration of ancient versions of writing, re-reading them, as in the same Ancient original, becomes a very difficult task for the doctrine of grammatology. While the fact that it has been preserved from the depths of ancient centuries without leaving various stains on the surfaces is a separate problem, it is undoubtedly one of the reasons for the discrepancy between the pronunciation and spelling, sound and marking of words of that era. The provisions of the ancient Turkic written texts of monuments that do not coincide with the original texts of sound, morphemic, lexeme, phrasal and phrasal systems translated by Turkologists of different periods are analyzed. A comparative analysis was carried out based on concrete examples of how the first line of the small script on the Kultegin monument was read and translated by scientists. As a result of a mutual comparison of the lines of the text, it was found that in the translated versions of the same sentence in the text of Kultegin, the double word in(i)ygün(ü)m (brothers-nephews) was translated by Turkologists in different versions. In addition, in studies and analyses of linguotextological examinations of texts of ancient Turkic written monuments, it is noted that one of the reasons why translations and sound inconsistencies can be directly related to differently interpreted and differently readable phonemic designations of individual sounds and pictographic symbols.

The Age of Datum or Data as a Methodological Paradigm

ABSTRACT This article illustrates how, like photography in the late nineteenth century, data often possesses an alluring appearance of objectivity which gives it affordance. It reflects on how data has altered methods of investigations and, while rejecting its use as a mere indexical trace of information that leads to unequivocal conclusions, advocates for the humanist’s intervention in directing how data is collected, prepared, used, and displayed. The article explores and illustrates three platforms: MediaWiki and its applications, including the Semantic Web; IIIF (International Image Interoperability Framework), a tool designed to replicate traditional image-comparative methodologies within a digital realm; and FromThePage, a text transcript platform. Finally, the conundrum of web archiving and data preservation is analysed, to reflect on how data has marked a paradigm shift in our perception, expectations, and understanding of methodologies in the humanities.

Enhancing Botanical Knowledge Graphs with Machine Learning

Integrating sparse and incomplete biodiversity data into a global, coherent data space and generating machine-readable data infrastructures is a challenge in biodiversity informatics. In recent years, biodiversity data researchers have started proposing Knowledge Graphs (KGs) as one approach to connecting biodiversity data worldwide (Page 2019), representing the connections between the what, when, and where of objects in natural history collections. At the Natural History Museum (NHM) we have constructed a KG of botanical specimens and collectors, encoded into numerical representations, and using a Relational Graph Convolutional Network (RGCN) (Schlichtkrull et al. 2018) to infer gaps in the KG, forging new connections between nodes. The datasets involved in our botanical KG project are NHM Botany Collector database (105,780 entities) and NHM Indian Region Botanical Specimen Dataset (110,043 entities with geographical information). Our KG with RGCN enables the structured and contextual data to be reasoned across the knowledge content, allowing us to dynamically update its representation according to its closely related neighbours. Our work will explain why and how the KG with RGCN can offer a better way to link digitised botanical data. We use the prototype KG to demonstrate its potential for modelling botanical data and provide a graphical representation for other machine learning applications. For example, the combination of KG with RGCN and Metric Learning (Xing et al. 2002, a form of Machine Learning generally used to automatically construct task-specific distance metrics) supports data completion via entity classification and link prediction for a subset of botanical specimens within a geographic region. These data augmentation models with KGs allow us to identify gaps in specimen provenance, and fill in missing data. After phase one training, our model can achieve 88% accuracy in entity classification and report a reasonable Mean Reciprocal Rank (MRR) in raw ranking link prediction for the Indian Region Botanical Specimen Dataset. Our research also evaluates the use of the KG and RGCN to improve post-OCR (Optical Character Recognition) correction algorithms as part of automatic specimen digitisation pipelines. This improves the accuracy of entity recognition on specimen label text identification and transcription, as part of machine learning natural language processing and human-in-the-loop transcription. Human-based transcription can be aided and improved by an interpretation recommendation system predicated on the specimen unit’s RGCN-inferred location in the KG. This methodology can also be used to explore the alignment of KGs from different institutions within the global biodiversity network, to identify the relative importance of collectors or determine strengths or gaps in different geographic regions or ecosystems, duplicate items in collections, or objects in collections that have potentially been misidentified.

Extensiveness of Higher Education Development Programme on Enabling Institutional Linkage to Ensure Quality University Graduates in the Northern Zone Tanzania

Institutional linkages has been a demand for all universities in the world. Higher Education Development Programme (HEDP) was meant to cater for this fundamental purpose. This study therefore aimed at finding out the extensiveness of HEDP on enabling institutional linkages of universities in the Northern Zone Tanzania. The study was anchored to the Value-Added-Theory. Convergent design under the mixed research paradigm lead the study. The target population for the study was 18,601 respondents from eight (8) Universities in the Northern Zone of Tanzania. This comprised of 5,118 final year bachelor degree students, 483 lecturers, 8 DVC-academics, 12,292 alumni and 100 employers. The study sample comprised of 697 respondents from which 511 were final year bachelor degree students, 48 lecturers, 4 DVC academics, 124 alumni and 10 employers. Sampling techniques included stratified random, purposive and automatic inclusion. Data collected through questionnaires, indepth interview guides and document analysis guides. Validity of quantitative data collection instruments was ensured through content and face validity while for qualitative was ensured through explanation of the purpose of study and ensuring equal time for each interview. Internal consistency of Likert type items was estimated through Cronbach Alpha, while the dependability of qualitative items was ensured through triangulation. Quantitative data was analyzed by using descriptive statistics where frequencies, percentages, and means were determined. Qualitative data was analyzed through transcription of texts, generate themes, interpret, discuss and making conclusions. The study found that, HEDP is to some extent known to students and alumni for its purpose of establishing linkages. The study concluded that HEDP has to the lower extent achieved the goal of ensuring institutional linkages. The study recommended that universities should conduct periodic review and reform programmes to cater for the needs of the current demands of 21st century soft skills.

ПРОФЕССИОНАЛЬНАЯ УДОВЛЕТВОРЕННОСТЬ МЕДИКОВ В ПЕРИОД ПАНДЕМИИ (НА МАТЕРИАЛАХ КОНТЕНТ-АНАЛИЗА ГЛУБИННЫХ ИНТЕРВЬЮ)

Objective of the study is to identify the opinions and assessments of medical professionals regarding the prestige of the medical profession, working conditions and professional burnout through the possibilities of content analysis of in-depth interviews. The methodological basis of the research. The content analysis of 40 text transcripts of in-depth interviews with medical workers of the Rostov region was carried out. The sample is solid. The indicators were recorded in the coding cards. The following categories of analysis are highlighted: perception of the prestige of the medical profession, a sense of professional burnout, satisfaction with working conditions, job satisfaction, professional status, the attitude of patients to doctors before the COVID-2019 pandemic, the attitude of patients during the COVID-2019 pandemic, the level of worry and anxiety, associations of physicians with the words “Red Zoneˮ. Research results. Content analysis on this topic made it possible to identify and analyze the opinions of doctors and average medical staff of the Rostov region, expressed in in-depth interviews, and draw conclusions about the presence or absence of satisfaction with working conditions, professional status, about assessing the prestige of the medical profession, about changing the nature of the patient-physician relationship, about sources, causes and consequences of worry, anxiety and professional burnout. Prospects of the study. The theoretical conclusions and practical results obtained can be further used in the course of the study of the prestige of the medical profession, the professional and social status of medical workers, their working conditions, professional burnout within such scientific branches as the sociology of professions, the sociology of medicine and healthcare.

Knowledge discovery of zakat administration worldwide from YouTube and Zoom via text mining

PurposeZakat (Islamic almsgiving) plays a considerable role in dealing with the socioeconomic issues in times of COVID-19 pandemic, and such roles have been widely discussed in virtual events. This paper aims to discover knowledge of the current global zakat administration from virtual events of zakat (e.g. webinars) on YouTube and Zoom via text mining approach.Design/methodology/approachThe authors purposefully sampled 12 experts from four different virtual zakat events on YouTube and Zoom. The automated text transcription software is used to pull the information from the sampled videos into text documents. A qualitative analysis is operated using text mining approach via machine learning tool (i.e. Orange Data Mining). Four research questions are developed under the Word Cloud visualisation, hierarchal clustering, topic modelling and graph and network theory.FindingsThe machine learning identifies the most important words, the relationship between the experts and their top words and discovers hidden themes from the sample. This finding is practically substantial for zakat stakeholders to understand the current issues of global zakat administration and to learn the applicable lessons from the current issues of zakat management worldwide.Research limitations/implicationsThis study does not establish a positivist generalisation from the findings because of the nature and objective of the study.Practical implicationsA policy implication is drawn pertaining to the legislation of zakat as an Islamic financial policy instrument for combating poverty in Muslim society.Social implicationsThis work supports the notion of “socioeconomic zakat”, implying that zakat as a religious obligation is important in shaping the social and economic processes of a Muslim community.Originality/valuesThis work marks the novelty in making sense of the unstructured data from virtual events on YouTube and Zoom in the Islamic social finance research.

A novel automated depression detection technique using text transcript

AbstractDepression is one of the most common mental illnesses, impacting billions of people worldwide. The lack of existing resources is impeding the country's economic prosperity. As a result, new approaches for detecting and treating mental diseases as well as reaching out to individuals are required so that people can overcome their daily challenges and become more productive. An automated depression detection system can greatly aid in clinical findings and early treatment of depression. Automatic detection, like in a clinical interview can be derived from various modalities that include video, audio, and text. Among these modalities, audio characteristics are the most commonly researched while text elements are seldom investigated. In the light of the above, this paper proposes a novel automated depression identification approach based on linguistic material gathered from patient interviews. The focus is to enhance both the accuracy and efficiency of detection. The proposed approach is made up of two parts: a Bidirectional Gated Recurrent Unit (BGRU) network for dealing with linguistic information and a fully coupled network that integrates the model outputs to measure the depressed state. The proposed approach is validated using Distress Analysis Interview Corpus‐Wizard‐of‐Oz interviews dataset. To evaluate the performance precision, recall, and F1 score are computed using the proposed approach and then the comparative analysis is done with the existing approaches. The proposed approach yielded an F1 score of 0.92, indicating the existence of depression as well as the projected severity level. It is realized from the generated results that the proposed approach has outperformed the previous ones. The proposed approach can not only automatically assess the severity of depression but also enhances both the accuracy and efficiency of detection. The proposed approach indicates the feasibility of BGRU over Long Short Term Memory by achieving exceptional results for recognition of depression.

Spoken Corpora of Slavic Languages

Spoken corpora are collections of transcribed and annotated audio and /or video recordings of languages or language varieties. The aim of this paper is to present an overview of 51 spoken corpora currently available for Slavic languages and dialects, in particular Belarusian, Bulgarian, Croatian, Czech, Polish, Russian, Slovak, Slovenian, Trasianka, Ukrainian/Rusyn. We identify three groups of corpora according to the type of lect: corpora of standard languages (spoken mainly in an urban environment and existing in both written and oral form), dialects (spoken mainly in a rural environment and unwritten), and bilingual varieties (we call bilingual varieties spoken as L2 by people with different L1 languages, as well as all varieties that evolved in a multilingual environment). We survey the corpora in terms of text registers, transcription, and principles of linguistic and extralinguistic annotation. In conclusion, we suggest a list of features that linguists should take into consideration when developing a spoken corpus. Many spoken corpora are currently being created for various Slavic lects, and their developers may use this overview as a source of information on different designs and solutions.