NDLI: Feature adaptation using linear spectro-temporal transform for robust speech recognition

Content Provider	ACM Digital Library
Author	Xiao, Xiong Nguyen, Duc Hoang Ha Chng, Eng Siong Li, Haizhou
Copyright Year	2016
Abstract	Spectral information represents short-term speech information within a frame of a few tens of milliseconds, while temporal information captures the evolution of speech statistics over consecutive frames. Motivated by the findings that human speech comprehension relies on the integrity of both the spectral content and temporal envelope of speech signal, we study a spectro-temporal transform framework that adapts run-time speech features to minimize the mismatch between run-time and training data, and its implementation that includes cross transform and cascaded transform. A Kullback-Leibler divergence based cost function is proposed to estimate the transform parameters. We conducted experiments on the REVERB Challenge 2014 task, where clean and multi-condition trained acoustic models are tested with real reverberant and noisy speech. We found that temporal information is important for reverberant speech recognition and the simultaneous use of spectral and temporal information for feature adaptation is effective. We also investigate the combination of the cross transform with fMLLR, the combination of batch, utterance and speaker mode adaptation, and multicondition adaptive training using proposed transforms. All experiments consistently report significant word error rate reductions.
Starting Page	1006
Ending Page	1019
Page Count	14
File Format	PDF
ISSN	23299290
e-ISSN	23299304
Volume Number	24
Issue Number	6
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-06-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Feature adaptation Linear transform Robust speech recognition Temporal filtering
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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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
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