NDLI: Divergence detection in a speech-excited in-service non-intrusive measurement device

Content Provider	IEEE Xplore Digital Library
Author	Ng, W.P. Elmirghani, J.M.H. Cryan, R.A. Yoong Choon Chang Broom, S.
Copyright Year	2000
Description	Author affiliation: Sch. of Eng., Northumbria Univ., Newcastle, UK (Ng, W.P.)
Abstract	This paper proposes new divergence detection techniques for implementation within in-service non-intrusive measurement devices (INMDs) in public switched telephone networks (PSTNs). The in-service non-intrusive measurement system of interest is used to monitor the delivered quality of speech (QoS) by monitoring the echoes in the telephony network. INMDs are usually based on a class of least mean square (LMS) digital adaptive filters (DAFs). The performance criterion is defined by the modelling convergence rate derived from the optimal Wiener weights, and the excitation for the DAFs is conversational speech. Four types of divergence detectors (DD) are proposed. These are energy divergence detectors (EDD), log energy divergence detectors (LDD), zero crossing divergence detectors (ZDD) and autocorrelation coefficient divergence detectors (ADD). The proposed DDs are based on the detection of voiced/unvoiced/silence periods and as such act as pattern classifiers. Experimental observations have shown that divergence occurs during the low energy unvoiced segments in high-noise environments. The tap-weight coefficients of the DAF are updated with the new value during the voiced segment while the update of the tap-weight coefficients during unvoiced segments of the speech is frozen. This result is then compared with the perfect divergence detector, which employs the Wiener weight theory. The DD techniques reported produce a significant improvement in the system's performance in a noise-impaired environment. Over one second adaptation (8000 samples) the energy divergence detector, the log energy divergence detector, the autocorrelation divergence detector and the zero crossing divergence detector gave model improvements of 16.93 dB, 15.81 db, 12.48 dB and 11.62 dB respectively at echo to noise ratio (e/N) of 0 dB. The proposed DDs compare well with the ideal (nonimplementable) Wiener DD which gives an improvement of 20.92 dB.
Starting Page	944
Ending Page	948
File Size	541299
Page Count	5
File Format	PDF
ISBN	0780362837
DOI	10.1109/ICC.2000.853637
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-06-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors Speech Telephony Monitoring Autocorrelation Working environment noise Least squares approximation Adaptive filters Convergence System performance
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

Non-intrusive whitening of speech using least mean square and divergence detection technique

Optimum variable step-size adaptation in a speech driven in-service non-intrusive measurement device

Parallel DAF measurement device (PDMD) for non-intrusive whitening of speech

Least-squares optimal variable step-size LMS for nonblind system identification with noise

Noise impaired echo path modelling using chaotic coded speech

A robust variable step size LMS-type algorithm: analysis and simulations

Performance comparison of adaptive algorithms applied to acoustic echo cancelling

A 32-point FFT based Noise Reduction Algorithm for Single Channel Speech Signals

Sub-band, dual-channel adaptive noise cancellation using normalised LMS

Divergence detection in a speech-excited in-service non-intrusive measurement device

Similar Documents

Non-intrusive whitening of speech using least mean square and divergence detection technique

Optimum variable step-size adaptation in a speech driven in-service non-intrusive measurement device

Parallel DAF measurement device (PDMD) for non-intrusive whitening of speech

Least-squares optimal variable step-size LMS for nonblind system identification with noise

Noise impaired echo path modelling using chaotic coded speech

A robust variable step size LMS-type algorithm: analysis and simulations

Performance comparison of adaptive algorithms applied to acoustic echo cancelling

A 32-point FFT based Noise Reduction Algorithm for Single Channel Speech Signals

Sub-band, dual-channel adaptive noise cancellation using normalised LMS

Divergence detection in a speech-excited in-service non-intrusive measurement device