{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T09:07:09Z","timestamp":1744276029402},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1007\/s11042-022-12937-6","type":"journal-article","created":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T21:02:25Z","timestamp":1649451745000},"page":"31245-31259","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Comparative analysis of Dysarthric speech recognition: multiple features and robust templates"],"prefix":"10.1007","volume":"81","author":[{"given":"Arunachalam","family":"Revathi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Nagakrishnan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N.","family":"Sasikaladevi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,8]]},"reference":[{"issue":"2014","key":"12937_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1687-4722-2014-5","volume":"5","author":"R Aihara","year":"2014","unstructured":"Aihara R, Takashima R, Takiguchi T et al (2014) A preliminary demonstration of exemplar-based voice conversion for articulation disorders using an individuality-preserving dictionary. J Audio Speech Music Proc 5(2014):1\u201310. https:\/\/doi.org\/10.1186\/1687-4722-2014-5","journal-title":"J Audio Speech Music Proc"},{"key":"12937_CR2","doi-asserted-by":"publisher","unstructured":"Aihara R, Takiguchi T, Ariki Y (2017) Phoneme-discriminative features for Dysarthric speech conversion. Proc Interspeech 2017:3374\u20133378 https:\/\/doi.org\/10.21437\/Interspeech.2017-664","DOI":"10.21437\/Interspeech.2017-664"},{"key":"12937_CR3","doi-asserted-by":"publisher","first-page":"20787","DOI":"10.1007\/s11042-019-7329-6","volume":"78","author":"R Arunachalam","year":"2019","unstructured":"Arunachalam R (2019) A strategic approach to recognizing the children's speech with hearing impairment: different sets of features and models. Multimed Tools Appl 78:20787\u201320808. https:\/\/doi.org\/10.1007\/s11042-019-7329-6","journal-title":"Multimed Tools Appl"},{"issue":"3","key":"12937_CR4","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1109\/TASLP.2016.2641904","volume":"25","author":"CSJ Doire","year":"2017","unstructured":"Doire CSJ, Brookes M, Naylor PA, Hicks CM, Betts D, Dmour MA, Jensen SH (2017) Single-Channel online enhancement of speech corrupted by reverberation and noise. IEEE\/ACM Trans Audio Speech Lang Proc 25(3):572\u2013587. https:\/\/doi.org\/10.1109\/TASLP.2016.2641904","journal-title":"IEEE\/ACM Trans Audio Speech Lang Proc"},{"issue":"6","key":"12937_CR5","doi-asserted-by":"publisher","first-page":"1109","DOI":"10.1109\/TASSP.1984.1164453","volume":"32","author":"Y Ephraim","year":"1984","unstructured":"Ephraim Y, Malah D (1984) Speech enhancement using a minimum mean square error short-time spectral amplitude estimator. IEEE Trans Acoust Speech Signal Process 32(6):1109\u20131121. https:\/\/doi.org\/10.1109\/TASSP.1984.1164453","journal-title":"IEEE Trans Acoust Speech Signal Process"},{"issue":"2","key":"12937_CR6","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1109\/TASSP.1985.1164550","volume":"33","author":"Y Ephraim","year":"1985","unstructured":"Ephraim Y, Malah D (1985) Speech enhancement using a minimum mean-square error log-spectral amplitude estimator. IEEE Trans Acoust Speech Signal Process 33(2):443\u2013445. https:\/\/doi.org\/10.1109\/TASSP.1985.1164550","journal-title":"IEEE Trans Acoust Speech Signal Process"},{"key":"12937_CR7","doi-asserted-by":"publisher","unstructured":"Espa\u00f1a-Bonet C, Fonollosa JA (2016) Automatic speech recognition with deep neuralnetworks for impaired speech. In: International Conference on Advances in Speech and Language Technologies forIberian Languages. Springer, Cham,\u00a0pp 97\u2013107.\u00a0https:\/\/doi.org\/10.1007\/978-3-319-49169-1_10","DOI":"10.1007\/978-3-319-49169-1_10"},{"key":"12937_CR8","doi-asserted-by":"crossref","unstructured":"Selouani SA, Dahmani H, Amami R, Hamam H (2012) Using speech rhythm knowledge to improve dysarthric speech recognition. Int J Speech Technol 15(1):57\u201364","DOI":"10.1007\/s10772-011-9104-6"},{"issue":"1","key":"12937_CR9","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1109\/TASL.2006.876858","volume":"15","author":"RM Hegde","year":"2007","unstructured":"Hegde RM, Murthy HA, Gadde VRR (2007) 'Significance of the modified group delay feature in speech recognition. IEEE Trans Audio Speech Lang Process 15(1):190\u2013202 https:\/\/ieeexplore.ieee.org\/document\/4032772\/","journal-title":"IEEE Trans Audio Speech Lang Process"},{"issue":"1","key":"12937_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1687-4722-2014-5","volume":"2014","author":"R Aihara","year":"2014","unstructured":"Aihara R, Takashima R, Takiguchi T, Ariki Y (2014) A preliminarydemonstration of exemplar-based voice conversion for articulation disorders using an individuality-preserving dictionary. Eurasip J Audio Speech Music Process 2014(1):1\u201310","journal-title":"Eurasip J Audio Speech Music Process"},{"key":"12937_CR11","doi-asserted-by":"publisher","first-page":"6009","DOI":"10.1109\/ICASSP.2018.8462290","volume-title":"Simulating Dysarthric Speech for Training Data Augmentation in Clinical Speech Applications","author":"Y Jiao","year":"2018","unstructured":"Jiao Y, Tu M, Berisha V, Liss J (2018) Simulating Dysarthric Speech for Training Data Augmentation in Clinical Speech Applications. 2018 IEEE international conference on acoustics, speech, and signal processing (ICASSP), Calgary, pp 6009\u20136013. https:\/\/doi.org\/10.1109\/ICASSP.2018.8462290"},{"key":"12937_CR12","doi-asserted-by":"crossref","unstructured":"Tu M, Berisha V, Liss J (2017) Interpretable objective assessment of dysarthric speech based on deep neural\u00a0networks. In Interspeech, pp 1849\u201331853","DOI":"10.21437\/Interspeech.2017-1222"},{"key":"12937_CR13","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1109\/CCECE.2004.1345019","volume-title":"Wavelet-based speech enhancement using two different threshold-based denoising algorithms","author":"A Lallouani","year":"2004","unstructured":"Lallouani A, Gabrea M, Gargour CS (2004) Wavelet-based speech enhancement using two different threshold-based denoising algorithms, 1st edn. Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513), Niagara Falls, Ontario, pp 315\u2013318. https:\/\/doi.org\/10.1109\/CCECE.2004.1345019","edition":"1"},{"issue":"13","key":"12937_CR14","doi-asserted-by":"publisher","first-page":"e108","DOI":"10.3346\/jkms.2019.34.e108","volume":"34","author":"SH Lee","year":"2019","unstructured":"Lee SH, Kim M, Seo HG, Oh BM, Lee G, Leigh JH (2019) Assessment of Dysarthria Using One-Word Speech Recognition with Hidden Markov Models. J Korean Med Sci 34(13):e108. Published 2019 April 8. https:\/\/doi.org\/10.3346\/jkms.2019.34.e108","journal-title":"J Korean Med Sci"},{"issue":"6","key":"12937_CR15","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1016\/j.specom.2008.01.003","volume":"50","author":"Y Lu","year":"2008","unstructured":"Lu Y, Loizou PC (2008) A geometric approach to spectral subtraction. Int J Speech Commun 50(6):453\u2013466. https:\/\/doi.org\/10.1016\/j.specom.2008.01.003","journal-title":"Int J Speech Commun"},{"key":"12937_CR16","doi-asserted-by":"publisher","first-page":"979","DOI":"10.1007\/s10772-019-09644-3","volume":"22","author":"A Revathi","year":"2019","unstructured":"Revathi A, Sasikaladevi N (2019) Hearing impaired speech recognition: Stockwell features and models. Int J Speech Technol 22:979\u2013991. https:\/\/doi.org\/10.1007\/s10772-019-09644-3","journal-title":"Int J Speech Technol"},{"key":"12937_CR17","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1007\/s10772-018-9546-1","volume":"21","author":"A Revathi","year":"2018","unstructured":"Revathi A, Sasikaladevi N, Nagakrishnan R, Jeyalakshmi C (2018) Robust emotion recognition from speech: Gamma tone features and models. Int J Speech Technol 21:723\u2013739. https:\/\/doi.org\/10.1007\/s10772-018-9546-1","journal-title":"Int J Speech Technol"},{"issue":"4","key":"12937_CR18","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1109\/TASL.2010.2072499","volume":"19","author":"F Rudzicz","year":"2011","unstructured":"Rudzicz F (2011) Articulatory knowledge in recognition of Dysarthric speech. IEEE Trans Audio Speech Lang Process 19(4):947\u2013960. https:\/\/doi.org\/10.1109\/TASL.2010.2072499","journal-title":"IEEE Trans Audio Speech Lang Process"},{"key":"12937_CR19","unstructured":"Islam MT, Shahnaz C, Zhu WP, Ahmad MO (2018) Enhancement of noisy speech with low speech distortion based on probabilistic geometric spectral subtraction. arXiv preprint arXiv:1802.05125"},{"issue":"6","key":"12937_CR20","doi-asserted-by":"publisher","first-page":"1163","DOI":"10.1016\/j.csl.2012.11.001","volume":"27","author":"F Rudzicz","year":"2013","unstructured":"Rudzicz F (2013) Adjusting dysarthric speech signals to be more intelligible. J Comp Speech Lang 27(6):1163\u20131177. https:\/\/doi.org\/10.1016\/j.csl.2012.11.001","journal-title":"J Comp Speech Lang"},{"key":"12937_CR21","doi-asserted-by":"crossref","unstructured":"Stark AP, W\u00f3jcicki KK, Lyons JG, Paliwal KK (2008) Noise driven short-time phase spectrum compensation procedure for speech enhancement. In: Ninth annual conference of the international speech communication association","DOI":"10.21437\/Interspeech.2008-163"},{"key":"12937_CR22","doi-asserted-by":"crossref","unstructured":"Kim H, Hasegawa-Johnson M, Perlman A, Gunderson J, Huang TS, Watkin K, Frame S (2008) Dysarthric speech database for universal access research. In: Ninth Annual Conference of the International Speech Communication Association","DOI":"10.21437\/Interspeech.2008-480"},{"key":"12937_CR23","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/s10772-011-9104-6","volume":"15","author":"S Sloane","year":"2012","unstructured":"Sloane S, Dahmani H, Amami R et al (2012) Using speech rhythm knowledge to improve dysarthric speech recognition. Int J Speech Technol 15:57\u201364. https:\/\/doi.org\/10.1007\/s10772-011-9104-6","journal-title":"Int J Speech Technol"},{"issue":"3","key":"12937_CR24","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1007\/s10772-018-9546-1","volume":"21","author":"A Revathi","year":"2018","unstructured":"Revathi A, Sasikaladevi N, Nagakrishnan R, Jeyalakshmi C (2018) Robust emotion recognition from speech: Gamma tone features and models. Int J Speech Technol 21(3):723\u2013739","journal-title":"Int J Speech Technol"},{"key":"12937_CR25","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1109\/EUSIPCO.2015.7362616","volume-title":"Feature extraction using pre-trained convolutive bottleneck nets for dysarthric speech recognition","author":"Y Takashima","year":"2015","unstructured":"Takashima Y, Nakashima T, Takiguchi T, Ariki Y (2015) Feature extraction using pre-trained convolutive bottleneck nets for dysarthric speech recognition. 2015 23rd European Signal Processing Conference (EUSIPCO), Nice, pp 1411\u20131415. https:\/\/doi.org\/10.1109\/EUSIPCO.2015.7362616"},{"key":"12937_CR26","doi-asserted-by":"publisher","first-page":"6395","DOI":"10.1109\/ICASSP.2019.8683803","volume-title":"End-to-end Dysarthric Speech Recognition Using Multiple Databases","author":"Y Takashima","year":"2019","unstructured":"Takashima Y, Takiguchi T, Ariki Y (2019) End-to-end Dysarthric Speech Recognition Using Multiple Databases. ICASSP 2019\u20132019 IEEE international conference on acoustics, speech, and signal processing (ICASSP), Brighton, pp 6395\u20136399. https:\/\/doi.org\/10.1109\/ICASSP.2019.8683803"},{"key":"12937_CR27","doi-asserted-by":"publisher","first-page":"352","DOI":"10.4103\/aian.AIAN_130_17","volume":"20","author":"MG Thoppil","year":"2017","unstructured":"Thoppil MG, Kumar CS, Kumar A, Amos J (2017) Speech signal analysis and pattern recognition in diagnosing dysarthria. Ann Indian Acad Neurol 20:352\u2013357 http:\/\/www.annalsofian.org\/text.asp?2017\/20\/4\/352\/217159","journal-title":"Ann Indian Acad Neurol"},{"key":"12937_CR28","unstructured":"Garofolo JS (1993) Timit acoustic phonetic continuous speech corpus. Linguistic Data Consortium, 1993"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12937-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-12937-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12937-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T05:09:48Z","timestamp":1661144988000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-12937-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,8]]},"references-count":28,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["12937"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-12937-6","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,8]]},"assertion":[{"value":"3 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 March 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 March 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 April 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"This article does not contain any studies with human participants.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"The authors have declared that no competing interest exists.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"All the authors declare that they have no conflict of\u00a0interest.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}}]}}