Relevant bibliographies by topics / Speech-to-text (STT)

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Academic literature on the topic 'Speech-to-text (STT)'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Speech-to-text (STT)"

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Duc, Chung Tran, Long Nguyen Duc, and Fadzil Hassan Mohd. "Development and testing of an FPT.AI-based voicebot." Bulletin of Electrical Engineering and Informatics 9, no. 6 (2020): 2388–95. https://doi.org/10.11591/eei.v9i6.2620.

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In recent years, voicebot has become a popular communication tool between humans and machines. In this paper, we will introduce our voicebot integrating text-to-speech (TTS) and speech-to-text (STT) modules provided by FPT.AI. This voicebot can be considered as a critical improvement of a typical chatbot because it can respond to human’s queries by both text and speech. FPT Open Speech, LibriSpeech datasets, and music files were used to test the accuracy and performance of the STT module. For the TTS module, it was tested by using text on news pages in both Vietnamese and English. To tes
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Journal, IJSREM. "A Review on Speech-to-Text." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem29004.

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The current era represents the global apex of groundbreaking advances in artificial intelligence (AI) technology, especially in the field of speech-to-text (STT).This review article focuses on the development of human skills through smooth, natural language interaction between people and robots, providing a thorough overview and exploration of the impressive advancements made in recent years. The study outlines a model intended to reinvent human-computer interaction, highlighting its ability to translate spoken language into text and carry out commands via a conversational, dynamic interface.
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Barkovska, Olesia. "RESEARCH INTO SPEECH-TO-TEXT TRANFROMATION MODULE IN THE PROPOSED MODEL OF A SPEAKER’S AUTOMATIC SPEECH ANNOTATION." Innovative Technologies and Scientific Solutions for Industries, no. 4 (22) (December 31, 2022): 5–13. http://dx.doi.org/10.30837/itssi.2022.22.005.

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The subject matter of the article is the module for converting the speaker’s speech into text in the proposed model of automatic annotation of the speaker’s speech, which has become more and more popular in Ukraine in the last two years, due to the active transition to an online form of communication and education as well as conducting workshops, interviews and discussing urgent issues. Furthermore, the users of personal educational platforms are not always able to join online meetings on time due to various reasons (one example can be a blackout), which explains the need to save the speakers’
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B, Mupini, Chaputsira S, and Sibanda Bk. "Survey on Speech to Text Modelling for the Shona Language." Survey on Speech to Text Modelling for the Shona Language 9, no. 1 (2024): 4. https://doi.org/10.5281/zenodo.10609671.

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Conversion of speech to text (STT) for various applications is of huge interest, which involves technological approaches which are innovative that should be applied to accommodate spoken languages in Africa. However, African countries are falling behind on the embracing of STT technologies, with Automatic Speech Recognition (ASR) having been done for popular East African languages. This has always kept transcription at a minimum and has also resulted in a  retard in the use of many African languages on a world- wide scale, with another problem being that a single  African language ma
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Yang, Hui Jae, Eun-Byel Oh, and Jung-Mee Kim. "Comparison of Automatic Speech Recognition System for School-aged Children’s Narratives: Naver Clova Speech and Google Speech-to-Text." Communication Sciences & Disorders 28, no. 1 (2023): 30–38. http://dx.doi.org/10.12963/csd.23952.

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Objectives: Language sample analysis (LSA) is a critical component of child language assessment. However, most clinicians consider LSA to be time consuming work. In particular, transcription is seen as an overwhelming task. Due to rapid technological advances, various automatic speech recognition systems have been developed. This study aimed to investigate the accuracy and the characteristics of two automatic speech recognition programs, Naver Clova Speech (Naver Clova) and Google Speech-to-Text (STT).Methods: A total of 40 school-aged children with typical development (TD) and children with l
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Dinata, Candra, Diyah Puspitaningrum, and Ernawati Erna. "IMPLEMENTASI TEKNIK DYNAMIC TIME WARPING (DTW) PADA APLIKASI SPEECH TO TEXT." JURNAL TEKNIK INFORMATIKA 10, no. 1 (2018): 49–58. http://dx.doi.org/10.15408/jti.v10i1.6816.

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ABSTRAK Suara/ucapan adalah salah satu cara kita sebagai manusia untuk berkomunikasi dan mengekspresikan diri. Speech to text (ucapan ke text), merupakan salah satu bidang sains computer yaitu bidang pengolahan suara. Speech to text (STT) adalah penerjemahan kalimat (kata yang diucapkan) ke dalam text. STT merupakan proses pengolahan suatu sinyal suara, mengekstrak fitur dari sinyal suara tersebut yang selanjutkan dibandingkan dengan hasil ekstraksi dari sinyal suara yang lain untuk dapat dikenali persamaannya. Penelitian ini merancang dan membangun suatu program aplikasi Speech to Text yang m
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G, Thimmaraja Yadava, G. Nagaraja B, Yogesh Kumaran S, C. Ramachandra A, and M. Arun Kumar N. "Development of Small Vocabulary Continuous Speech-to-Text System for Kannada Language/Dialects." Indian Journal of Science and Technology 15, no. 45 (2022): 2476–81. https://doi.org/10.17485/IJST/v15i45.1884.

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Abstract <strong>Objectives:</strong>&nbsp;To develop a speech-to-text (STT) system using Kaldi speech recognition toolkit for continuous Kannada language/dialects.&nbsp;<strong>Methods:</strong>&nbsp;A continuous Kannada speech data is collected from 100 speakers/farmers of Karnataka state in field. The lexicon/dictionary and set of phonemes for Kannada language/dialects are created and transcribed the collected speech data using transcriber tool. The ASR models are developed at different phoneme levels using Kaldi.&nbsp;<strong>Findings:</strong>&nbsp;In this work, an effort is made to devel
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Schwarz, Nikolai, Khia A. Johnson, and Molly Babel. "Exploring the variable efficacy of Google speech-to-text with spontaneous bilingual speech in Cantonese and English." Journal of the Acoustical Society of America 150, no. 4 (2021): A357. http://dx.doi.org/10.1121/10.0008580.

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With the growth of Automatic Speech Recognition (ASR) and voice user interface software, it is important to test for efficacy across different language varieties and identify sources of bias. Recent work assessing ASR efficacy and bias implicates factors like race, gender, dialect, and age as leading to different efficacy rates. Multilingualism presents another source of variation that ASR systems must grapple with, ranging from code-switching to phonetic variation both within and across speakers. Thus, variable ASR performance is likely exacerbated for multilingual communities. Using a sponta
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p, Ms SANDHUSTA,. "Speech -To -Text Translation Using Hugging Face Model." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30348.

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The internet has revolutionized communication, but it's particularly challenging for those with hearing impairments. A multilingual speech-to-text conversion system using Hugging Face algorithms is being developed to assist these individuals in various tasks. This system, which uses advanced neural network models and natural language processing algorithms, will translate spoken language into text, enabling seamless communication and engagement in various contexts, thereby enhancing the quality of life for those with hearing impairments. Keywords—Speech-to-Text (STT)
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Tran, Duc Chung, Duc Long Nguyen, and Mohd Fadzil Hassan. "Development and testing of an FPT.AI-based voicebot." Bulletin of Electrical Engineering and Informatics 9, no. 6 (2020): 2388–95. http://dx.doi.org/10.11591/eei.v9i6.2620.

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In recent years, voicebot has become a popular communication tool between humans and machines. In this paper, we will introduce our voicebot integrating text-to-speech (TTS) and speech-to-text (STT) modules provided by FPT.AI. This voicebot can be considered as a critical improvement of a typical chatbot because it can respond to human’s queries by both text and speech. FPT Open Speech, LibriSpeech datasets, and music files were used to test the accuracy and performance of the STT module. For the TTS module, it was tested by using text on news pages in both Vietnamese and English. To test the
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Books on the topic "Speech-to-text (STT)"

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Kon'kov, Vladimir, and Tat'yana Surikova. Linguistic foundations of business communication. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1062745.

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In the textbook, in section I, the norms and standards of the official business style, genre templates, rules for preparing documents, and the basics of business ethics are set out in a simple, accessible form. It highlights aspects of business communication that, despite their importance, are not reflected in manuals on similar topics. This is information about the problems of adequate understanding of information, working with business terminology, and also gives an assessment of business jargon. Special attention is paid to the forms of information compression in the business text. The theo
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Singh, Anushka. Sedition in Liberal Democracies. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199481699.001.0001.

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Liberal democracies claim to give constitutional and legal protection of varying degrees to the right to free speech of which political speech and the right to dissent are extensions. Within the right to freedom of expression, however, some category of speeches do not enjoy protection as they are believed to be ‘injurious’ to society. One such unprotected form of political speech is sedition which is criminalized for the repercussions it may have on the authority of the government and the state. The cases registered in India in recent months under the law against sedition show that the law in
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Kasabov, Nikola. Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering. The MIT Press, 1996. http://dx.doi.org/10.7551/mitpress/3071.001.0001.

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In a clear and accessible style, Kasabov describes rule-based and connectionist techniques and then their combinations, with fuzzy logic included, showing the application of the different techniques to a set of simple prototype problems, which makes comparisons possible. A particularly strong feature of the text is that it is filled with applications in engineering, business, and finance. AI problems that cover most of the application-oriented research in the field (pattern recognition, speech and image processing, classification, planning, optimization, prediction, control, decision making, a
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Perry, Seth. Bible Culture and Authority in the Early United States. Princeton University Press, 2018. http://dx.doi.org/10.23943/princeton/9780691179131.001.0001.

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This book is a wide-ranging exploration of the place of the Christian Bible in America in the decades after the Revolution. Attending to both theoretical concerns about the nature of scriptures and to the precise historical circumstances of a formative period in American history, the book argues that the Bible was not a “source” of authority in early America, as is often said, but rather a site of authority: a cultural space for editors, commentators, publishers, preachers, and readers to cultivate authoritative relationships. While paying careful attention to early national bibles as material
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Ufimtseva, Nataliya V., Iosif A. Sternin, and Elena Yu Myagkova. Russian psycholinguistics: results and prospects (1966–2021): a research monograph. Institute of Linguistics, Russian Academy of Sciences, 2021. http://dx.doi.org/10.30982/978-5-6045633-7-3.

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The monograph reflects the problems of Russian psycholinguistics from the moment of its inception in Russia to the present day and presents its main directions that are currently developing. In addition, theoretical developments and practical results obtained in the framework of different directions and research centers are described in a concise form. The task of the book is to reflect, as far as it is possible in one edition, firstly, the history of the formation of Russian psycholinguistics; secondly, its methodology and developed methods; thirdly, the results obtained in different research
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Book chapters on the topic "Speech-to-text (STT)"

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Wong Shuk Man, Cecilia, and Patrick Chu Chun-Kau. "Improving Cantonese speech-to-text (STT) recognition by using a pronunciation model." In Applying Technology to Language and Translation. Routledge, 2024. https://doi.org/10.4324/9781003399261-6.

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Duran, Logan Wong, Mithil Darur, and Kok Zuea Tang. "Development and Prototyping of a Speech-To-Text (STT) Model and Lip Recognition Software for Tiny Machine Learning (TinyML) Systems." In Proceedings in Technology Transfer. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3770-6_39.

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Cope, Bill, Mary Kalantzis, and Anastasia Olga (Olnancy) Tzirides. "Chapter 13. Meaning without borders." In Studies in Bilingualism. John Benjamins Publishing Company, 2024. http://dx.doi.org/10.1075/sibil.66.13cop.

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“Translanguaging” is a concept that connects with older traditions of analysis in linguistics and practices in language pedagogy, while at the same time making some distinctions that justify the creation of a new word. This chapter begins by tracing roots of the idea of translanguaging in its intellectual predecessors and affiliates: code switching, translation, bilingualism, multilingualism, hybridity, and multiliteracies. In the sections that follow, we set out to extend the terms of this discussion by introducing another concept, “transposition,” designed to cast the net wider than language
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Pasupuleti, Murali Krishna. "Decoding Conversational AI: From Text to Context with NLP." In Natural Language Processing Unveiled: Bridging Human-AI Communication. National Education Services, 2024. http://dx.doi.org/10.62311/nesx/97814.

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Abstract: This chapter delves into the realm of Conversational AI, an innovative fusion of Artificial Intelligence (AI) and Natural Language Processing (NLP) that is transforming the way humans interact with machines. By enabling machines to understand, process, and generate human language in a contextually relevant manner, Conversational AI facilitates seamless, intuitive, and meaningful dialogues between humans and technology. From the foundational technologies like advanced language models and speech recognition to the design principles guiding dialogue management and context handling, this
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"Text-to-Speech (TTS) Synthesis." In The Electrical Engineering Handbook - Six Volume Set. CRC Press, 2018. http://dx.doi.org/10.1201/9781315219677-22.

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Narupiyakul Lalita, Sirinaovakul Booncharoen, and Cercone Nick. "Thai Syllable Analysis for Rule-Based Text to Speech System." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2013. https://doi.org/10.3233/978-1-61499-258-5-139.

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TTS system initially transforms text input into a sequence of sound symbols. The complexity of Thai requires about several hundred of rules including main and specific rules to derive most pronunciations for the rule-based approach. Our proposed rule-based system is based on the syllable structure analysis. To increase the quality of TTS, an exception dictionary to cover anomalous pronunciations and using rule reference engine to determine sentence structure are included in the system. The phonetic generation and speech generation by mapping table are sequential steps to transform a set of pho
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Miller, Jim, and Regina Weinert. "Focus Constructions." In Spontaneous Spoken Language. Oxford University PressOxford, 1998. http://dx.doi.org/10.1093/oso/9780198236566.003.0005.

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Abstract In Chapters 2, 3, and 4 we have examined the differences between spoken and written languages with respect to clauses and noun phrases. In both spontaneous speech and in written language, clauses are organized into larger chunks. In writing, clauses are first combined into sentences and sentences are then put together into texts. In spontaneous speech speakers combine clauses into larger units but, as argued in Chapter 2, it is not fruitful to analyse spontaneous speech in terms of sentences. Writers produce letters, novels, business and legal documents, textbooks, and so on. They typ
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Moore, Colette. "Before Quotation Marks." In Speech Representation in the History of English. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190918064.003.0002.

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One convention for indicating represented speech, prevalent in the late sixteenth through the early eighteenth centuries, was to use parentheses to set off interjecting quotation markers such as he said. Unlike modern quotation marks, however, the parentheses do not mark the words of represented speech but rather mark the quotative clause that interrupts the utterance, modeling a different understanding of how to indicate discursive shifts in text. This investigation qualitatively examines the conditioning factors that constrain the usage and the interdependence of different kinds of organizat
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Wongkia Wararat, Naruedomkul Kanlaya, and Cercone Nick. "I-Math: an Intelligent Accessible Mathematics system for People with Visual Impairment." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2013. https://doi.org/10.3233/978-1-61499-258-5-83.

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We propose an intelligent accessible mathematics approach, called i-Math for people with visual impairment on reading math expressions in Thai. Math expressions in various forms were investigated for developing a set of rules to correctly read the math expressions. Our proposed approach has revealed it is possible to construct a practically automatic math expressions reading system by suitable technologies of speech processing. The i-Math system prototype was tested to generate the accurate speech (intelligibility and overall speech quality) for a math problem sample set and its usage (user sa
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Sánchez, Àlex, Sergio Montoya, Josep Escrig, and Ivan Huerta. "Automatic Catalan Keyword Spotting Database Generator." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia240421.

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Home assistants are essential today, but they typically support only popular languages. Promoting products that enhance underrepresented languages is crucial for preservation. Using a home assistant in one’s native language, such as Catalan, is a significant step toward this goal. Keyword spotting (KWS) and speech recognition are two potential solutions. The lightweight architecture of KWS models is promising for low-powered edge devices in domotic environments. However, there is a lack of resources to train such models, especially for Catalan. This paper presents a solution using forced align
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Conference papers on the topic "Speech-to-text (STT)"

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Minixhofer, Christoph, Ondřej Klejch, and Peter Bell. "TTSDS - Text-to-Speech Distribution Score." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832178.

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Tseng, Cindy, Yun Tang, and Vijendra Raj Apsingekar. "Transducer Consistency Regularization For Speech to Text Applications." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832230.

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Wang, Hankun, Chenpeng Du, Yiwei Guo, Shuai Wang, Xie Chen, and Kai Yu. "Attention-Constrained Inference For Robust Decoder-Only Text-to-Speech." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832301.

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Wang, Changhan, Yun Tang, Xutai Ma, Anne Wu, Dmytro Okhonko, and Juan Pino. "Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq." In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing: System Demonstrations. Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.aacl-demo.6.

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Guo, Haohan, Fenglong Xie, Kun Xie, et al. "SoCodec: A Semantic-Ordered Multi-Stream Speech Codec For Efficient Language Model Based Text-to-Speech Synthesis." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832247.

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Yamauchi, Kazuki, Yuki Saito, and Hiroshi Saruwatari. "Cross-Dialect Text-to-Speech In Pitch-Accent Language Incorporating Multi-Dialect Phoneme-Level Bert." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832155.

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Ma, Min, Gary Wang, Kyle Kastner, Isaac Caswell, Charles Yoon, and Andrew Rosenberg. "Enhancing Low-Resource Spoken Language Identification Via Cross-Modality Retrieval and Cross-Lingual Text-to-Speech Synthesis." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832238.

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Wu, Haibin, Xiaofei Wang, Sefik Emre Eskimez, et al. "Laugh Now Cry Later: Controlling Time-Varying Emotional States of Flow-Matching-Based Zero-Shot Text-To-Speech." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832181.

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Karl, Anderson Luiz, Guilherme Sales Fernandes, Leonardo Augusto Pires, Yvens R. Serpa, and Carlos Caminha. "Synthetic AI Data Pipeline for Domain-Specific Speech-to-Text Solutions." In Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Sociedade Brasileira de Computação, 2024. https://doi.org/10.5753/stil.2024.245336.

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In this article, we propose a pipeline to fine-tune domain-specific Speech-to-Text (STT) models using synthetic data generated by Artificial Intelligence (AI). Our methodology eliminates the need for manually labelled audio data, which is expensive and difficult to obtain, by generating domain-specific data with a Large Language Model (LLM) combined with multiple Text-to-Speech (TTS) solutions. We applied our pipeline to the radiology domain and compared the results with different approaches based on the availability of domain-specific data, varying from the total absence of domain-specific da
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de Lima, Pedro L. S., and Cláudio E. C. Campelo. "Disfluency Detection and Removal in Speech Transcriptions via Large Language Models." In Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Sociedade Brasileira de Computação, 2024. https://doi.org/10.5753/stil.2024.245417.

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The field of Automatic Speech Recognition (ASR) has significantly expanded within the technological landscape due to its extensive use in sectors such as education, healthcare, and customer service. Many modern applications depend on analyzing spoken content through Speech-to-Text (STT) conversion models. However, transcriptions produced by these systems often contain undesirable elements, such as word repetitions and the prolongation of certain sounds, known as disfluencies or linguistic crutches. These elements can negatively affect the quality of automatic content analysis by Natural Langua
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Reports on the topic "Speech-to-text (STT)"

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Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.

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The article investigates functional techniques of extralinguistic expression in multimedia texts; the effectiveness of figurative expressions as a reaction to modern events in Ukraine and their influence on the formation of public opinion is shown. Publications of journalists, broadcasts of media resonators, experts, public figures, politicians, readers are analyzed. The language of the media plays a key role in shaping the worldview of the young political elite in the first place. The essence of each statement is a focused thought that reacts to events in the world or in one’s own country. Th
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