NDLI: Formant-Based Robust Voice Activity Detection

Content Provider	IEEE Xplore Digital Library
Author	In-Chul Yoo Hyeontaek Lim Dongsuk Yook
Copyright Year	2014
Abstract	Voice activity detection (VAD) can be used to distinguish human speech from other sounds, and various applications can benefit from VAD-including speech coding and speech recognition. To accurately detect voice activity, the algorithm must take into account the characteristic features of human speech and/or background noise. In many real-life applications, noise frequently occurs in an unexpected manner, and in such situations, it is difficult to determine the characteristics of noise with sufficient accuracy. As a result, robust VAD algorithms that depend less on making correct noise estimates are desirable for real-life applications. Formants are the major spectral peaks of the human voice, and these are highly useful to distinguish vowel sounds. The characteristics of the spectral peaks are such that, these peaks are likely to survive in a signal after severe corruption by noise, and so formants are attractive features for voice activity detection under low signal-to-noise ratio (SNR) conditions. However, it is difficult to accurately extract formants from noisy signals when background noise introduces unrelated spectral peaks. Therefore, this paper proposes a simple formant-based VAD algorithm to overcome the problem of detecting formants under conditions with severe noise. The proposed method achieves a much faster processing time and outperforms standard VAD algorithms under various noise conditions. The proposed method is robust against various types of noise and produces a light computational load, so it is suitable for use in various applications.
Starting Page	2238
Ending Page	2245
Page Count	8
File Size	1433249
File Format	PDF
ISSN	23299290
Volume Number	23
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise measurement Signal to noise ratio Training data Speech processing voice activity detection (VAD) Formants spectral peaks
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Signal Processing Instrumentation Speech and Hearing Electrical and Electronic Engineering Computational Mathematics Media Technology

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

Formant-based robust voice activity detection

Boosting Contextual Information for Deep Neural Network Based Voice Activity Detection

Speech Analysis With the Strong Uncorrelating Transform

Dual-Microphone Voice Activity Detection Technique Based on Two-Step Power Level Difference Ratio

Speech analysis with the strong uncorrelating transform

Super-audible voice activity detection

Audio-visual voice activity detection using diffusion maps

Low complexity formant estimation adaptive feedback cancellation for hearing aids using pitch based processing

On Training Targets for Supervised Speech Separation

Formant-Based Robust Voice Activity Detection

Similar Documents

Formant-based robust voice activity detection

Boosting Contextual Information for Deep Neural Network Based Voice Activity Detection

Speech Analysis With the Strong Uncorrelating Transform

Dual-Microphone Voice Activity Detection Technique Based on Two-Step Power Level Difference Ratio

Speech analysis with the strong uncorrelating transform

Super-audible voice activity detection

Audio-visual voice activity detection using diffusion maps

Low complexity formant estimation adaptive feedback cancellation for hearing aids using pitch based processing

On Training Targets for Supervised Speech Separation

Formant-Based Robust Voice Activity Detection