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pro vyhledávání: '"C. S. Anoop"'
Autor:
C. S. Anoop, A. G. Ramakrishnan
Publikováno v:
IEEE Access, Vol 11, Pp 82050-82064 (2023)
Indian languages share a lot of overlap in acoustic and linguistic content. Though different languages use different writing systems, the phoneme sets logically overlap. Most of these languages are low-resourced, lacking enough annotated speech data
Externí odkaz:
https://doaj.org/article/e90b9cedb76848559cb336ce6c998f23
Publikováno v:
Frontiers in Computer Science, Vol 3 (2021)
Alzheimer’s dementia (AD) is a type of neurodegenerative disease that is associated with a decline in memory. However, speech and language impairments are also common in Alzheimer’s dementia patients. This work is an extension of our previous wor
Externí odkaz:
https://doaj.org/article/0cc8a6f60dc54f0a9270f6a292458afd
Autor:
K. Jishnu, C. S. Anoop
Publikováno v:
2023 International Conference on Power, Instrumentation, Energy and Control (PIECON).
Publikováno v:
2022 IEEE 8th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA).
Autor:
A. G. Ramakrishnan, C S Anoop
Publikováno v:
2021 National Conference on Communications (NCC).
Sanskrit is one of the Indian languages which fares poorly, with regard to the development of language-based tools. In this work, we build a connectionist temporal classification (CTC) based end-to-end large vocabulary continuous speech recognition s
Publikováno v:
SLT
In this work, we explore the effectiveness of log-Mel spectrogram and MFCC features for Alzheimer’s dementia (AD) recognition on ADReSS challenge dataset. We use three different deep neural networks (DNN) for AD recognition and mini-mental state ex
Autor:
C. S. Anoop, A. G. Ramakrishnan
Publikováno v:
Neural Information Processing ISBN: 9783030922696
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1c738e732df41059ec30c0af44ee5f0
https://doi.org/10.1007/978-3-030-92270-2_46
https://doi.org/10.1007/978-3-030-92270-2_46
Autor:
C. S. Anoop, A. G. Ramakrishnan
Publikováno v:
2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT).
This paper presents our work on building a speaker independent, large vocabulary continuous speech recognition system for Sanskrit using HMM Toolkit (HTK). To our knowledge, this is the maiden attempt on a Sanskrit automatic speech recognizer. A Sans