NDLI: Proposing two speaker adaptaion methods for deep neural network based speech recognition systems

Content Provider	IEEE Xplore Digital Library
Author	Ansari, Z. Salehi, S.A.S.
Copyright Year	2014
Description	Author affiliation: Biomed. Eng. Dept., Amirkabi Univ. of Technol., Tehran, Iran (Salehi, S.A.S.) \|\| Biomed. Eng. Dept., Amirkabir Univ. of Technol., Tehran, Iran (Ansari, Z.)
Abstract	Many researches have done to develop speech recognition systems in the past decades. However, their performance in speaker variabilities lags behind that of human recognition system. In order to solve this problem, speaker adaptation methods have proposed. These methods adapt either the acoustic model parameters or the input features of the speech recognition systems to improve their performance. In this article, two speaker adaptation methods for deep neural network based speech recognition systems are proposed. In the first method, feature vectors of each speaker are adapted nonlinearly after some forward-backward iterations. In the other one, the speech recognition system is modified in order to be able to adapt dynamically in speaker variabilities. This method, unlike other model adaptation methods, does not need to any adaptation data and adapts the model online. Experiments on FARSDAT dataset demonstrate that these methods improve phone recognition accuracy rate by 2% and 6%.
Starting Page	452
Ending Page	457
File Size	330961
Page Count	6
File Format	PDF
e-ISBN	9781479953592
DOI	10.1109/ISTEL.2014.7000746
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-09
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Adaptation models Deep neural networks Neurons Hidden Markov models Nonlinear normalization Speech recognition Speech Acoustics Speaker adaptation Speaker recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in