NDLI: Fast segment search for corpus-based speech enhancement based on speech recognition technology

Content Provider	IEEE Xplore Digital Library
Author	Ogawa, A. Kinoshita, K. Hori, T. Nakatani, T. Nakamura, A.
Copyright Year	2014
Abstract	Corpus-based speech enhancement has received increasing attention recently since it shows high enhancement performance in highly non-stationary noisy environments by precisely modeling the long-term temporal dynamics of speech. However, it has a disadvantage in that the cost is very high for searching the longest matching clean speech segments from a multi-condition parallel speech corpus. This paper proposes a fast segment search method for corpus-based speech enhancement. It is mainly based on two techniques derived from speech recognition technology. The first is an A* search like segment evaluation function for accurately finding the longest matching segments. The second is a tree and linear connected search space for efficiently sharing the segment likelihood calculations. In the experiments for non-stationary noisy observations using the 26 multi-condition TIMIT parallel speech corpus, the proposed search method found the segments almost in real-time without degrading the quality of the enhanced speech. Our method was about 7 to 13 times faster than the conventional segment search method.
Sponsorship	IEEE Signal Process. Soc.
Starting Page	1557
Ending Page	1561
File Size	211622
Page Count	5
File Format	PDF
ISBN	9781479928934
DOI	10.1109/ICASSP.2014.6853859
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-04
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech Speech enhancement Noise measurement Search methods Speech recognition Signal to noise ratio speech recognition technology Corpus-based speech enhancement fast segment search longest matching segments
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

A Corpus-Based Approach to Speech Enhancement From Nonstationary Noise

Degraded word recognition based on segmental signal-to-noise ratio weighting

Residual noise removal on beamforming for robust hands-free speech recognition

Noise power spectrum estimation based on weak speech protection for speech enhancement

Speech Enhancement Using MMSE Estimation and Spectral Subtraction Methods

Noise robust exemplar matching with coupled dictionaries for single-channel speech enhancement

Robust speech-based happiness recognition

Evaluation of speech enhancement based on pre-image iterations using automatic speech recognition

The effect of phase information in speech enhancement and speech recognition

Fast segment search for corpus-based speech enhancement based on speech recognition technology

Similar Documents

A Corpus-Based Approach to Speech Enhancement From Nonstationary Noise

Degraded word recognition based on segmental signal-to-noise ratio weighting

Residual noise removal on beamforming for robust hands-free speech recognition

Noise power spectrum estimation based on weak speech protection for speech enhancement

Speech Enhancement Using MMSE Estimation and Spectral Subtraction Methods

Noise robust exemplar matching with coupled dictionaries for single-channel speech enhancement

Robust speech-based happiness recognition

Evaluation of speech enhancement based on pre-image iterations using automatic speech recognition

The effect of phase information in speech enhancement and speech recognition

Fast segment search for corpus-based speech enhancement based on speech recognition technology