Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition
In this paper, we discuss our research work in Telugu Indian language speech data for building a large language vocabulary to build Telugu speech recognition system. We have collected speech research data around 2628 utterances in Telugu language among 14 Indian regional languages as part of Speech...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/11079596/ |
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| author | M. Rama Rajeswari Suryakanth V. Gangashetty |
| author_facet | M. Rama Rajeswari Suryakanth V. Gangashetty |
| author_sort | M. Rama Rajeswari |
| collection | DOAJ |
| description | In this paper, we discuss our research work in Telugu Indian language speech data for building a large language vocabulary to build Telugu speech recognition system. We have collected speech research data around 2628 utterances in Telugu language among 14 Indian regional languages as part of Speech Quality Control Project under Bhashini-NLTM (National Language Translation Mission) in collaboration with IIT Madras. In this research work, we discuss our methodology for the collection of Telugu data and developing Telugu speech database. In our paper, we present the preliminary results that are obtained by building speech recognition using the acoustic models created on Telugu language database by implementing Kaldi toolkit for speech in building ASR in Telugu language. The proposed hybrid DNN-HMM acoustic model implemented to build Telugu ASR in Kaldi achieved a WER score of 0. 7% when the weight of the inverse_language_model is 17 in the test data set of the Telugu speech database. In the process of our work, some of the ASR models, methods and speech processing performance metrics that we used in ASR in order to maintain quality corpus are discussed. |
| format | Article |
| id | doaj-art-2daaf9e5d5354b95896da164d4dcbfe7 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-2daaf9e5d5354b95896da164d4dcbfe72025-08-20T03:13:39ZengIEEEIEEE Access2169-35362025-01-011312275212276810.1109/ACCESS.2025.358866411079596Hybrid DNN-HMM-Based Approach for Telugu Language Speech RecognitionM. Rama Rajeswari0https://orcid.org/0009-0002-8997-5527Suryakanth V. Gangashetty1https://orcid.org/0000-0001-6745-4363Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, IndiaDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, IndiaIn this paper, we discuss our research work in Telugu Indian language speech data for building a large language vocabulary to build Telugu speech recognition system. We have collected speech research data around 2628 utterances in Telugu language among 14 Indian regional languages as part of Speech Quality Control Project under Bhashini-NLTM (National Language Translation Mission) in collaboration with IIT Madras. In this research work, we discuss our methodology for the collection of Telugu data and developing Telugu speech database. In our paper, we present the preliminary results that are obtained by building speech recognition using the acoustic models created on Telugu language database by implementing Kaldi toolkit for speech in building ASR in Telugu language. The proposed hybrid DNN-HMM acoustic model implemented to build Telugu ASR in Kaldi achieved a WER score of 0. 7% when the weight of the inverse_language_model is 17 in the test data set of the Telugu speech database. In the process of our work, some of the ASR models, methods and speech processing performance metrics that we used in ASR in order to maintain quality corpus are discussed.https://ieeexplore.ieee.org/document/11079596/ASRHMMMFCCTelugu languageacoustic modellanguage model |
| spellingShingle | M. Rama Rajeswari Suryakanth V. Gangashetty Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition IEEE Access ASR HMM MFCC Telugu language acoustic model language model |
| title | Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition |
| title_full | Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition |
| title_fullStr | Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition |
| title_full_unstemmed | Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition |
| title_short | Hybrid DNN-HMM-Based Approach for Telugu Language Speech Recognition |
| title_sort | hybrid dnn hmm based approach for telugu language speech recognition |
| topic | ASR HMM MFCC Telugu language acoustic model language model |
| url | https://ieeexplore.ieee.org/document/11079596/ |
| work_keys_str_mv | AT mramarajeswari hybriddnnhmmbasedapproachfortelugulanguagespeechrecognition AT suryakanthvgangashetty hybriddnnhmmbasedapproachfortelugulanguagespeechrecognition |