NDLI: A Speech Endpoint Detection Method Based on Wavelet Coefficient Variance and Sub-Band Amplitude Variance

Content Provider	IEEE Xplore Digital Library
Author	Xueying Zhang Zhefeng Zhao Gaofeng Zhao
Copyright Year	2006
Description	Author affiliation: Coll. of Inf. Eng., Taiyuan Univ. of Technol. (Xueying Zhang; Zhefeng Zhao; Gaofeng Zhao)
Abstract	Speech endpoint detection is one key technology for speech recognition. The paper proposed two kinds of endpoint detection methods: the algorithm based on the wavelet coefficient variance and the algorithm based on the sub-band average amplitude variance. Speech signal with noise was decomposed by wavelet to investigate the statistic characteristics of wavelet coefficient and sub-band amplitude. Their variances were extracted as feature to make endpoint detection. The first method's adaptability is better than the second method, but its complexity is higher than the second method. So the synthesized speech end-point detection algorithm that is consisted of above two methods was proposed. It can select a suitable way to make operation according to noise type. Thus it can increase system efficiency and implement endpoint detection. Simulations were made under different signal-to-noise ratios and the results show that this method is efficient to segment noisy speech even at a low signal-to-noise ratio
Sponsorship	IEEE ICIC Int. National Natural Sci. Found. of China Beijing Jiaotong Univ. Kaosiung Univ. of Appl. Sci
Starting Page	83
Ending Page	86
File Size	131893
Page Count	4
File Format	PDF
ISBN	0769526160
DOI	10.1109/ICICIC.2006.400
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech recognition Speech enhancement Feature extraction Speech synthesis Signal synthesis Statistics Detection algorithms Wavelet coefficients Signal to noise ratio Noise level
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 speech endpoint detection method based on wavelet coefficient variance.

Noise robust speaker verification using mel-frequency discrete wavelet coefficients and parallel model compensation

An Improved Speech Endpoint Detection Based on Spectral Subtraction and Adaptive Sub-band Spectral Entropy

A speech endpoint detection algorithm based on wavelet transforms

An Improved Endpoint Detection Algorithm with Low Signal-to-Noise Ratio

Noise-resistant feature extraction using 2D techniques

Performance evaluation of front-end algorithms for robust speech recognition

Speech endpoint detection algorithm for Uyghur based on acoustic frequency feature

A new pitch detection method

A Speech Endpoint Detection Method Based on Wavelet Coefficient Variance and Sub-Band Amplitude Variance

Similar Documents

A speech endpoint detection method based on wavelet coefficient variance.

Noise robust speaker verification using mel-frequency discrete wavelet coefficients and parallel model compensation

An Improved Speech Endpoint Detection Based on Spectral Subtraction and Adaptive Sub-band Spectral Entropy

A speech endpoint detection algorithm based on wavelet transforms

An Improved Endpoint Detection Algorithm with Low Signal-to-Noise Ratio

Noise-resistant feature extraction using 2D techniques

Performance evaluation of front-end algorithms for robust speech recognition

Speech endpoint detection algorithm for Uyghur based on acoustic frequency feature

A new pitch detection method

A Speech Endpoint Detection Method Based on Wavelet Coefficient Variance and Sub-Band Amplitude Variance