Relevant bibliographies by topics / ASR-system

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'ASR-system'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "ASR-system"

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de Steiger, Richard N., Jacqueline R. Hang, Lisa N. Miller, Stephen E. Graves, and David C. Davidson. "Five-Year Results of the ASR XL Acetabular System and the ASR Hip Resurfacing System." Journal of Bone and Joint Surgery-American Volume 93, no. 24 (2011): 2287–93. http://dx.doi.org/10.2106/jbjs.j.01727.

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Udofia, Paul Moses. "A Critical and Optimal Location for an Autonomous Security Robot in Niger Delta, Nigeria." Advanced Materials Research 403-408 (November 2011): 4944–48. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4944.

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Autonomous Security robots (ASR) can be used to provide security where and when it is too hazardous to the human security guards. The paper is suggesting the introduction/incorporation of ASR into the Niger Delta security system (NDSS). Critical points (where ASR are needed) within the zones are identified based on the past security records. These records served as baseline data which regression lines are generated and produced into some future dates. How many ASR are required at a particular time in the system? Is the number feasible? What are the likely obstructions of the project? These are
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Qian, Zhaopeng, Li Wang, Shaochuan Zhang, Chan Liu, and Haijun Niu. "Mandarin Electrolaryngeal Speech Recognition Based on WaveNet-CTC." Journal of Speech, Language, and Hearing Research 62, no. 7 (2019): 2203–12. http://dx.doi.org/10.1044/2019_jslhr-s-18-0313.

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Purpose The application of Chinese Mandarin electrolaryngeal (EL) speech for laryngectomees has been limited by its drawbacks such as single fundamental frequency, mechanical sound, and large radiation noise. To improve the intelligibility of Chinese Mandarin EL speech, a new perspective using the automatic speech recognition (ASR) system was proposed, which can convert EL speech into healthy speech, if combined with text-to-speech. Method An ASR system was designed to recognize EL speech based on a deep learning model WaveNet and the connectionist temporal classification (WaveNet-CTC). This s
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Lin, Yu-Yi, Wei-Zhong Zheng, Wei Chung Chu, et al. "A Speech Command Control-Based Recognition System for Dysarthric Patients Based on Deep Learning Technology." Applied Sciences 11, no. 6 (2021): 2477. http://dx.doi.org/10.3390/app11062477.

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Voice control is an important way of controlling mobile devices; however, using it remains a challenge for dysarthric patients. Currently, there are many approaches, such as automatic speech recognition (ASR) systems, being used to help dysarthric patients control mobile devices. However, the large computation power requirement for the ASR system increases implementation costs. To alleviate this problem, this study proposed a convolution neural network (CNN) with a phonetic posteriorgram (PPG) speech feature system to recognize speech commands, called CNN–PPG; meanwhile, the CNN model with Mel
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Fontan, Lionel, Isabelle Ferrané, Jérôme Farinas, et al. "Automatic Speech Recognition Predicts Speech Intelligibility and Comprehension for Listeners With Simulated Age-Related Hearing Loss." Journal of Speech, Language, and Hearing Research 60, no. 9 (2017): 2394–405. http://dx.doi.org/10.1044/2017_jslhr-s-16-0269.

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Purpose The purpose of this article is to assess speech processing for listeners with simulated age-related hearing loss (ARHL) and to investigate whether the observed performance can be replicated using an automatic speech recognition (ASR) system. The long-term goal of this research is to develop a system that will assist audiologists/hearing-aid dispensers in the fine-tuning of hearing aids. Method Sixty young participants with normal hearing listened to speech materials mimicking the perceptual consequences of ARHL at different levels of severity. Two intelligibility tests (repetition of w
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Neri, Ambra, Catia Cucchiarini, and Helmer Strik. "The effectiveness of computer-based speech corrective feedback for improving segmental quality in L2 Dutch." ReCALL 20, no. 2 (2008): 225–43. http://dx.doi.org/10.1017/s0958344008000724.

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AbstractAlthough the success of automatic speech recognition (ASR)-based Computer Assisted Pronunciation Training (CAPT) systems is increasing, little is known about the pedagogical effectiveness of these systems. This is particularly regrettable because ASR technology still suffers from limitations that may result in the provision of erroneous feedback, possibly leading to learning breakdowns. To study the effectiveness of ASR-based feedback for improving pronunciation, we developed and tested a CAPT system providing automatic feedback on Dutch phonemes that are problematic for adult learners
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Hai, Xinhe, Kaviya Aranganadin, Cheng-Cheng Yeh, et al. "A Self-Evaluated Bilingual Automatic Speech Recognition System for Mandarin–English Mixed Conversations." Applied Sciences 15, no. 14 (2025): 7691. https://doi.org/10.3390/app15147691.

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Bilingual communication is increasingly prevalent in this globally connected world, where cultural exchanges and international interactions are unavoidable. Existing automatic speech recognition (ASR) systems are often limited to single languages. However, the growing demand for bilingual ASR in human–computer interactions, particularly in medical services, has become indispensable. This article addresses this need by creating an application programming interface (API)-based platform using VOSK, a popular open-source single-language ASR toolkit, to efficiently deploy a self-evaluated bilingual
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Phuengrod, Siriluk, Panita Wannapiroon, and Prachyanun Nilsook. "Distributed Communicative Language Training Platform Using Automatic Speech Recognition Technology for Smart University." International Journal of Emerging Technologies in Learning (iJET) 18, no. 24 (2023): 96–111. http://dx.doi.org/10.3991/ijet.v18i24.40619.

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The purpose of this research is to achieve the following objectives: 1) Synthesize documents and international research on the characteristics of a smart university. 2) Synthesize the processes of distributed communicative language training (DCLT). 3) Design the system architecture of a DCLT platform that utilizes automatic speech recognition (ASR) technology for a smart university. 4) Evaluate the appropriateness of a DCLT platform that utilizes ASR technology for a smart university. Nine experts were selected for this research. They were required to have more than five years of relevant expe
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Si, Mei, Omar Cobas, and Michael Fababeir. "Lexical Error Guard: Leveraging Large Language Models for Enhanced ASR Error Correction." Machine Learning and Knowledge Extraction 6, no. 4 (2024): 2435–46. http://dx.doi.org/10.3390/make6040120.

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Error correction is a vital element in modern automatic speech recognition (ASR) systems. A significant portion of ASR error correction work is closely integrated within specific ASR systems, which creates challenges for adapting these solutions to different ASR frameworks. This research introduces Lexical Error Guard (LEG), which leverages the extensive pre-trained knowledge of large language models (LLMs) and employs instructional learning to create an adaptable error correction system compatible with various ASR platforms. Additionally, a parameter-efficient fine-tuning method is utilized u
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Hamidi, Mohamed, Hassan Satori, Ouissam Zealouk, and Naouar Laaidi. "Estimation of ASR Parameterization for Interactive System." International Journal of Natural Computing Research 10, no. 1 (2021): 28–40. http://dx.doi.org/10.4018/ijncr.2021010103.

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In this study, the authors explore the integration of speaker-independent automatic Amazigh speech recognition technology into interactive applications to extract data remotely from a distance database. Based on the combined interactive voice response (IVR) and automatic speech recognition (ASR) technologies, the authors built an interactive speech system to allow users to interact with the interactive system through voice commands. The hidden Markov models (HMMs), Gaussian mixture models (GMMs), and Mel frequency spectral coefficients (MFCCs) are used to develop a speech system based on the t
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Dissertations / Theses on the topic "ASR-system"

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Keerio, Ayaz. "Acoustic analysis of Sindhi speech : a pre-curser for an ASR system." Thesis, University of Sussex, 2011. http://sro.sussex.ac.uk/id/eprint/6325/.

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The functional and formative properties of speech sounds are usually referred to as acoustic-phonetics in linguistics. This research aims to demonstrate acoustic-phonetic features of the elemental sounds of Sindhi, which is a branch of the Indo-European family of languages mainly spoken in the Sindh province of Pakistan and in some parts of India. In addition to the available articulatory-phonetic knowledge; acoustic-phonetic knowledge has been classified for the identification and classification of Sindhi language sounds. Determining the acoustic features of the language sounds helps to bring
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Wilson, Aaron Benjamin. "Enhancement of Polar WRF atmospheric and surface processes: An annual simulation." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1268066611.

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Gong, XiangQi. "Ellection markup language (EML) based tele-voting system." Thesis, University of the Western Cape, 2009. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_5841_1350999620.

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Elections are one of the most fundamental activities of a democratic society. As is the case in any other aspect of life, developments in technology have resulted changes in the voting procedure from using the traditional paper-based voting to voting by use of electronic means, or e-voting. E-voting involves using different forms of electronic means like<br>voting machines, voting via the Internet, telephone, SMS and digital interactive television. This thesis concerns voting by telephone, or televoting, it starts by giving a brief overview and evaluation of various models and technologies tha
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Skantze, Daniel. "Ljuddesign för rumsmetaforbaserade talgränssnitt." Thesis, Linköping University, Department of Computer and Information Science, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1874.

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<p>In this paper, a navigation support approach for speech-only interaction based on auditory icons for room-based designs is presented, i.e. naturally occurring sounds that have a natural mapping to the system's underlying design metaphor. In contrast to many recent investigations that have focused on multi-modal or augmented reality systems, this paper concerns a unimodal speech and sound-only system. An auditory icon based prototype system for buildings maintenance support using a room-based metaphor was developed. The design was evaluated in a comparison with earcons and no-sound designs.
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Toledo, Thiago Ferreira de. "Desenvolvimento de um protótipo de sistema web para elaboração de laudos médicos utilizando sistemas de reconhecimento automático de fala." Universidade Estadual do Oeste do Paraná, 2017. http://tede.unioeste.br/handle/tede/3399.

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Submitted by Miriam Lucas (miriam.lucas@unioeste.br) on 2018-02-22T14:55:33Z No. of bitstreams: 2 Thiago_Ferreira_ Toledo_2017.pdf: 4330728 bytes, checksum: 73f5158965bc4e02f9124a14dff04241 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2018-02-22T14:55:33Z (GMT). No. of bitstreams: 2 Thiago_Ferreira_ Toledo_2017.pdf: 4330728 bytes, checksum: 73f5158965bc4e02f9124a14dff04241 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-08-18<br>The overall purpose of automatic speech recogni
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Іванов, І. О. "Розробка та моделювання адаптивної саморегулюючої системи управління інвестиційним портфелем". Thesis, Одеський національний економічний університет, 2020. http://dspace.oneu.edu.ua/jspui/handle/123456789/12590.

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В першому розділі кваліфікаційної роботи досліджено теоретичні аспекти сутності інвестиційного портфелю та особливостей його формування, визначено найбільш оптимальний підхід щодо класифікації активів, проведено оцінку інвестиційних якостей агрегованих на класи та підкласи активів на основі фінансових інструментів, що їх репрезентують, проаналізовано відмінності між активними та пасивними стратегіями управління інвестиційним портфелем та їх недоліки. В другому розділі проаналізовано існуючі системи управління інвестиційним портфелем, проведено регресійний аналіз факторів впливу на динаміку ак
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Groenewald, Ilse. "A bio-behavioural investigation into the role of the cholinergic system in stress / Ilse Groenewald." Thesis, North-West University, 2006. http://hdl.handle.net/10394/1558.

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Laryea, Joycelyn, and Nipunika Jayasundara. "Automatic Speech Recognition System for Somali in the interest of reducing Maternal Morbidity and Mortality." Thesis, Högskolan Dalarna, Mikrodataanalys, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:du-34436.

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Developing an Automatic Speech Recognition (ASR) system for the Somali language, though not novel, is not actively explored; hence there has been no success in a model for conversational speech. Neither are related works accessible as open-source. The unavailability of digital data is what labels Somali as a low resource language and poses the greatest impediment to the development of an ASR for Somali. The incentive to develop an ASR system for the Somali language is to contribute to reducing the Maternal Mortality Rate (MMR) in Somalia. Researchers acquire interview audio data regarding mate
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Sklar, Alexander Gabriel. "Channel Modeling Applied to Robust Automatic Speech Recognition." Scholarly Repository, 2007. http://scholarlyrepository.miami.edu/oa_theses/87.

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In automatic speech recognition systems (ASRs), training is a critical phase to the system?s success. Communication media, either analog (such as analog landline phones) or digital (VoIP) distort the speaker?s speech signal often in very complex ways: linear distortion occurs in all channels, either in the magnitude or phase spectrum. Non-linear but time-invariant distortion will always appear in all real systems. In digital systems we also have network effects which will produce packet losses and delays and repeated packets. Finally, one cannot really assert what path a signal will take, and
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Liang, Hong-Bin, and 梁鴻彬. "The Personal Name Modeling in Mandarin ASR System." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/qvmxf3.

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碩士<br>國立交通大學<br>電機工程學系<br>107<br>There are two purposes in the paper, one is training an efficient ASR system, the other is improving the OOV problem caused by the personal name, and we want to recognize it for the purpose of making transcription of different kind of speech data. Name recognition data is also an important training data for the NLP. The paper base on the environment of Kaldi speech recognition toolkit. In the acoustic model part, we use many different kind of neural network such as CNN, LSTM, TDNN and DNN to transform the speech information into phone sequence. In the language
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Book chapters on the topic "ASR-system"

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Ronny, Ronny, Aamir Shakoor, Fabio Brugnara, and Roberto Gretter. "The FBK ASR System for Evalita 2011." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35828-9_32.

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Marcinek, Milan, Jozef Juhar, and Anton Cizmar. "Phoneme Based ASR System for Slovak SpeechDat Database." In Text, Speech and Dialogue. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44805-5_31.

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Ngueajio, Mikel K., and Gloria Washington. "Hey ASR System! Why Aren’t You More Inclusive?" In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21707-4_30.

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Bera, Anup, and Aanchal Agarwal. "Bias Detection and Mitigation Framework for ASR System." In Signals and Communication Technology. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89994-2_2.

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Kipyatkova, Irina, Ildar Kagirov, Mikhail Dolgushin, and Alexandra Rodionova. "Towards a Livvi-Karelian End-to-End ASR System." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-77961-9_4.

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Lopes, José, Maxine Eskenazi, and Isabel Trancoso. "Incorporating ASR Information in Spoken Dialog System Confidence Score." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28885-2_45.

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Calvo, Marcos, Lluís-F. Hurtado, Fernando García, and Emilio Sanchis. "Combining Several ASR Outputs in a Graph-Based SLU System." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25751-8_66.

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Rousseau, Anthony, Gilles Boulianne, Paul Deléglise, Yannick Estève, Vishwa Gupta, and Sylvain Meignier. "LIUM and CRIM ASR System Combination for the REPERE Evaluation Campaign." In Text, Speech and Dialogue. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10816-2_53.

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Mulfari, Davide, Gabriele Meoni, Marco Marini, and Luca Fanucci. "Towards a Deep Learning Based ASR System for Users with Dysarthria." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94277-3_86.

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Bougares, Fethi, Mickael Rouvier, Nathalie Camelin, Paul Deléglise, and Yannick Estève. "An Investigation of Single-Pass ASR System Combination for Spoken Language Understanding." In Statistical Language and Speech Processing. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39593-2_5.

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Conference papers on the topic "ASR-system"

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Hock, Vincent F., Michael K. McInerney, J. Chad Pierce, and Heather E. Creason. "Demonstration of Electro-Osmotic Pulse (EOP) Technology to Mitigate Alkali-Silica Reaction in Concrete Pavement." In CONFERENCE 2024. AMPP, 2024. https://doi.org/10.5006/c2024-21198.

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Abstract Many private-sector, federal government, and Department of Defense (DoD) facilities experience the problem of concrete deteriorating via alkali-silica reaction (ASR). ASR is a form of concrete corrosion that slowly deteriorates concrete from the inside by forming highly expansive gels that cause cracking and swelling of the concrete matrix. This paper summarizes the results of a project that evaluated Electro-Osmotic Pulse (EOP) technology to mitigate ASR in an area of the visitor’s ramp at Campbell Army Airfield. An EOP system was designed, installed, and monitored in a concrete pave
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Sun, Yujia, Jinxin He, Yi Zhang, et al. "The Fawaispeech System for Multi-Channel Speech Recognition in ICMC-ASR Challenge." In 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW). IEEE, 2024. http://dx.doi.org/10.1109/icasspw62465.2024.10627314.

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Helgadóttir, Inga R., Anna Björk Nikulásdóttir, Michal Borský, Judy Y. Fong, Róbert Kjaran, and Jón Guðnason. "The Althingi ASR System." In Interspeech 2019. ISCA, 2019. http://dx.doi.org/10.21437/interspeech.2019-1248.

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Ma, Rao, Mengjie Qian, Mark J. F. Gales, and Kate M. Knill. "Adapting an Unadaptable ASR System." In INTERSPEECH 2023. ISCA, 2023. http://dx.doi.org/10.21437/interspeech.2023-1899.

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Jia, Yanan. "A Deep Learning System for Domain-Specific Speech Recognition." In 8th International Conference on Software Engineering. Academy & Industry Research Collaboration, 2023. http://dx.doi.org/10.5121/csit.2023.131213.

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As human-machine voice interfaces provide easy access to increasingly intelligent machines, many state-of-theart automatic speech recognition (ASR) systems are proposed. However, commercial ASR systems usually have poor performance on domain-specific speech especially under low-resource settings. The author works with pre-trained DeepSpeech2 and Wav2Vec2 acoustic models to develop benefit-specific ASR systems. The domainspecific data are collected using proposed semi-supervised learning annotation with little human intervention. The best performance comes from a fine-tuned Wav2Vec2-Large-LV60
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Cardoso, Walcir, and Danial Mehdipour-Kolour. "Writing with automatic speech recognition: Examining user’s behaviours and text quality (lexical diversity)." In EuroCALL 2023: CALL for all Languages. Editorial Universitat Politécnica de Valéncia, 2023. http://dx.doi.org/10.4995/eurocall2023.2023.16997.

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This study explores the potential of Automatic Speech Recognition (ASR) as a writing tool by investigating user behaviours (strategies henceforth) and text quality (lexical diversity) when users engage with the technology. Thirty English second language writers dictated texts into an ASR system (Google Voice Typing) while also using optional additional input devices, such as keyboards and mice. Analysis of video recordings and field observations revealed four strategies employed by users to produce texts: use of ASR exclusively, ASR in tandem with keyboarding, ASR followed by keyboarding, and
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Soltau, Hagen, George Saon, Brian Kingsbury, et al. "The IBM 2006 Gale Arabic ASR System." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366921.

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Barkani, Fatima, Hassan Satori, and Mohamed Hamidi. "Cough Detection System Based on ASR-HMM." In 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS). IEEE, 2020. http://dx.doi.org/10.1109/icds50568.2020.9268765.

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Hifny, Yasser, Steve Renals, and Neil D. Lawrence. "A hybrid Maxent/HMM based ASR system." In Interspeech 2005. ISCA, 2005. http://dx.doi.org/10.21437/interspeech.2005-143.

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Çetin, Özgür, Harriet J. Nock, Katrin Kirchhoff, Jeff A. Bilmes, and Mari Ostendorf. "The 2001 GMTK-based SPINE ASR system." In 7th International Conference on Spoken Language Processing (ICSLP 2002). ISCA, 2002. http://dx.doi.org/10.21437/icslp.2002-31.

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Reports on the topic "ASR-system"

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Michalsen, Mandy, Anthony Bednar, Matthew Farthing, Jim Szecsody, and Fred Day-Lewis. Floridan Aquifer System (FAS) aquifer material collection and screening : investigating arsenic fate and transport under lab-simulated aquifer storage and recovery (ASR) conditions in the FAS—Task A report. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49788.

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The US Army Engineer Research Development Center is leading a laboratory study to quantify arsenic release that could occur during large-scale aquifer storage and recovery (ASR) operations in the anoxic Floridan Aquifer System (FAS). FAS materials containing arsenic must be collected and preserved under anoxic conditions to complete the laboratory study. This report describes collection, preservation, and initial characterization results of FAS material collected. Analysis of water surrounding the FAS material during storage detected some arsenic, suggesting arsenic presence in the solids. In-
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Pressel, Kyle, Thijs Heus, Yunyan Zhang, et al. Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES): Workshop Report. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2004980.

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Pressel, Kyle, Thijs Heus, Yunyan Zhang, et al. Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) Workshop Report. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2202486.

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Koch, Dorothy, Sally McFarlane, Shaima Nasiri, et al. Accelerated Climate Modeling for Energy (ACME) – Atmospheric Radiation Measurement (ARM) Climate Research Facility – Atmospheric System Research (ASR) Coordination Workshop, October 21–22, 2015. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1471413.

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Zhang, Zhibo, and David Mechem. Final DOE-ASR Report for the Project “Characterizing the Variation and Covariation of Cloud Microphysical Properties and Implications for Simulation of Subgrid-scale Warm-Rain Processes in Earth System Models”. Office of Scientific and Technical Information (OSTI), 2023. https://doi.org/10.2172/2217548.

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