TY - GEN
T1 - Kannada Speech Recognition System for Aphasic people
AU - Aishwarya, Jaya
AU - Kundapur, Poornima Panduranga
AU - Kumar, Sampath
AU - Hareesha, K. S.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/30
Y1 - 2018/11/30
N2 - Aphasia is a loss or an impairment of language that is due to brain damage, which affects the production of speech and the ability to read or write. his lead to the necessity of large human resources in terms of a speech therapist and physicians, caretakers, etc. Having an automatic computer/mobile-based technology for the detection, evaluation and providing timely feedback would give a great benefit to the medical community immensely. It also speeds up the process with minimum efforts. This has motivated us to create a knowledge base to build machine learning model to understand and learn from the available data for an accurate prediction. The Automatic Speech Recognition (ASR) technology has the potential to enable individuals with aphasia using computer based conversion of spoken word to a text form. This would make it possible for language therapy software to provide feedback about the correctness of the user's spoken utterances or to engage the user in spoken dialog practice or other language therapy activities. ASR hence must be developed further in order to make it feasible for people with speech impairments.
AB - Aphasia is a loss or an impairment of language that is due to brain damage, which affects the production of speech and the ability to read or write. his lead to the necessity of large human resources in terms of a speech therapist and physicians, caretakers, etc. Having an automatic computer/mobile-based technology for the detection, evaluation and providing timely feedback would give a great benefit to the medical community immensely. It also speeds up the process with minimum efforts. This has motivated us to create a knowledge base to build machine learning model to understand and learn from the available data for an accurate prediction. The Automatic Speech Recognition (ASR) technology has the potential to enable individuals with aphasia using computer based conversion of spoken word to a text form. This would make it possible for language therapy software to provide feedback about the correctness of the user's spoken utterances or to engage the user in spoken dialog practice or other language therapy activities. ASR hence must be developed further in order to make it feasible for people with speech impairments.
UR - https://www.scopus.com/pages/publications/85060019930
UR - https://www.scopus.com/pages/publications/85060019930#tab=citedBy
U2 - 10.1109/ICACCI.2018.8554657
DO - 10.1109/ICACCI.2018.8554657
M3 - Conference contribution
AN - SCOPUS:85060019930
T3 - 2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018
SP - 1753
EP - 1756
BT - 2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018
Y2 - 19 September 2018 through 22 September 2018
ER -