Review of Toolkit to Build Automatic Speech Recognition Models

G. P. Raghudathesh; C. B. Chandrakala; B. Dinesh Rao

doi:10.1007/978-981-19-4052-1_45

Review of Toolkit to Build Automatic Speech Recognition Models

G. P. Raghudathesh, C. B. Chandrakala, B. Dinesh Rao

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Speech is one of the most significant types of communication between human beings. It is beginning to be a preferred means for communication between machines and humans. The mechanism of transforming human speech into its equivalent textual format is known as speech recognition. Various toolkits are being used to automate the process of speech-to-text conversion, and this process is referred to as automatic speech recognition (ASR). The usage of the ASR system is becoming prevalent with the implementation of human–machine interaction. Numerous speech-based assistive systems are available today used in several different areas. This paper provides insight into the ASR domain and toolkit used in ASR system—HTK, CMU Sphinx, Kaldi, and Julius with their comparative analysis in terms of installation, ease of use, and accuracy assessment.

Original language	English
Title of host publication	Emerging Technologies in Data Mining and Information Security - Proceedings of IEMIS 2022
Editors	Paramartha Dutta, Satyajit Chakrabarti, Abhishek Bhattacharya, Soumi Dutta, Celia Shahnaz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	449-459
Number of pages	11
ISBN (Print)	9789811940514
DOIs	https://doi.org/10.1007/978-981-19-4052-1_45
Publication status	Published - 2023
Event	3rd International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2022 - Kolkata, India Duration: 23-02-2022 → 25-02-2022

Publication series

Name	Lecture Notes in Networks and Systems
Volume	490
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	3rd International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2022
Country/Territory	India
City	Kolkata
Period	23-02-22 → 25-02-22

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-981-19-4052-1_45

Cite this

Raghudathesh, G. P., Chandrakala, C. B., & Rao, B. D. (2023). Review of Toolkit to Build Automatic Speech Recognition Models. In P. Dutta, S. Chakrabarti, A. Bhattacharya, S. Dutta, & C. Shahnaz (Eds.), Emerging Technologies in Data Mining and Information Security - Proceedings of IEMIS 2022 (pp. 449-459). (Lecture Notes in Networks and Systems; Vol. 490). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-4052-1_45

Raghudathesh, G. P. ; Chandrakala, C. B. ; Rao, B. Dinesh. / Review of Toolkit to Build Automatic Speech Recognition Models. Emerging Technologies in Data Mining and Information Security - Proceedings of IEMIS 2022. editor / Paramartha Dutta ; Satyajit Chakrabarti ; Abhishek Bhattacharya ; Soumi Dutta ; Celia Shahnaz. Springer Science and Business Media Deutschland GmbH, 2023. pp. 449-459 (Lecture Notes in Networks and Systems).

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title = "Review of Toolkit to Build Automatic Speech Recognition Models",

abstract = "Speech is one of the most significant types of communication between human beings. It is beginning to be a preferred means for communication between machines and humans. The mechanism of transforming human speech into its equivalent textual format is known as speech recognition. Various toolkits are being used to automate the process of speech-to-text conversion, and this process is referred to as automatic speech recognition (ASR). The usage of the ASR system is becoming prevalent with the implementation of human–machine interaction. Numerous speech-based assistive systems are available today used in several different areas. This paper provides insight into the ASR domain and toolkit used in ASR system—HTK, CMU Sphinx, Kaldi, and Julius with their comparative analysis in terms of installation, ease of use, and accuracy assessment.",

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doi = "10.1007/978-981-19-4052-1_45",

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Raghudathesh, GP, Chandrakala, CB & Rao, BD 2023, Review of Toolkit to Build Automatic Speech Recognition Models. in P Dutta, S Chakrabarti, A Bhattacharya, S Dutta & C Shahnaz (eds), Emerging Technologies in Data Mining and Information Security - Proceedings of IEMIS 2022. Lecture Notes in Networks and Systems, vol. 490, Springer Science and Business Media Deutschland GmbH, pp. 449-459, 3rd International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2022, Kolkata, India, 23-02-22. https://doi.org/10.1007/978-981-19-4052-1_45

Review of Toolkit to Build Automatic Speech Recognition Models. / Raghudathesh, G. P.; Chandrakala, C. B.; Rao, B. Dinesh.

Emerging Technologies in Data Mining and Information Security - Proceedings of IEMIS 2022. ed. / Paramartha Dutta; Satyajit Chakrabarti; Abhishek Bhattacharya; Soumi Dutta; Celia Shahnaz. Springer Science and Business Media Deutschland GmbH, 2023. p. 449-459 (Lecture Notes in Networks and Systems; Vol. 490).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Speech is one of the most significant types of communication between human beings. It is beginning to be a preferred means for communication between machines and humans. The mechanism of transforming human speech into its equivalent textual format is known as speech recognition. Various toolkits are being used to automate the process of speech-to-text conversion, and this process is referred to as automatic speech recognition (ASR). The usage of the ASR system is becoming prevalent with the implementation of human–machine interaction. Numerous speech-based assistive systems are available today used in several different areas. This paper provides insight into the ASR domain and toolkit used in ASR system—HTK, CMU Sphinx, Kaldi, and Julius with their comparative analysis in terms of installation, ease of use, and accuracy assessment.

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Raghudathesh GP, Chandrakala CB, Rao BD. Review of Toolkit to Build Automatic Speech Recognition Models. In Dutta P, Chakrabarti S, Bhattacharya A, Dutta S, Shahnaz C, editors, Emerging Technologies in Data Mining and Information Security - Proceedings of IEMIS 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 449-459. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-19-4052-1_45

Review of Toolkit to Build Automatic Speech Recognition Models

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