NDLI: Predictive and mel-scale binary vector quantization of variable dimension spectral magnitude

Content Provider	IEEE Xplore Digital Library
Author	Yong Duk Cho Moo Young Kim Kondoz, A.
Copyright Year	2000
Description	Author affiliation: CCSR, Surrey Univ., Guildford, UK (Yong Duk Cho)
Abstract	In sinusoidal speech coding, the LP-spectral envelope is limited in its spectral accuracy if the order of the LP-model is not high enough. Thus the quantization of the residual spectrum of the low order LP-model may be desirable for good quality speech reconstruction. From the investigation of the magnitude of the LP-residual spectrum, it is found that the predictive coding scheme is useful for removing coding redundancy considerably. The problem of having a variable number of harmonics due to pitch changes can be alleviated by a length warping technique. Subsequently, the residual spectrum of the predictive coding is represented by mel-scale binary vector quantizer (MBVQ), which quantizes the residual spectrum by splitting harmonic bands of variable dimension into a fixed dimension, based on mel scale, and representing each element of the code vector as a binary value. The optimal code vector for the MBVQ can be derived by minimizing an error measure, defined as the weighted square-sum of the difference between original and synthesized spectral envelopes. From the performance evaluation, it is shown that the predictive-coded MBVQ with low order LP can obtain the effect of considerably high order LP-model. Additionally, the proposed method can be implemented with very low computational complexity in time and space.
Starting Page	1459
Ending Page	1462
File Size	353653
Page Count	4
File Format	PDF
ISBN	0780362934
ISSN	15206149
DOI	10.1109/ICASSP.2000.861894
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-06-05
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Distortion measurement Predictive coding Interpolation Predictive models Human computer interaction Speech coding Redundancy Computational complexity Vocoders
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 novel particle based approach for robust speech spectrum Vector Quantization

Low bit rate LPC vocoders using vector quantization and interpolation

Variable-dimension vector quantization of speech spectra for low-rate vocoders

Multiple stage vector quantization for speech coding

Vector quantization-lattice vector quantization of speech LPC coefficients

Variable-Dimension Vector Quantization of Speech Spectra for Low-Rate Vocoders (1994)

Recent developments in vector quantization for speech processing

A combined quantization-interpolation scheme for very low bit rate coding of speech LSP parameters

Application of sorted codebook vector quantization to spectral coding of speech

Predictive and mel-scale binary vector quantization of variable dimension spectral magnitude

Similar Documents

A novel particle based approach for robust speech spectrum Vector Quantization

Low bit rate LPC vocoders using vector quantization and interpolation

Variable-dimension vector quantization of speech spectra for low-rate vocoders

Multiple stage vector quantization for speech coding

Vector quantization-lattice vector quantization of speech LPC coefficients

Variable-Dimension Vector Quantization of Speech Spectra for Low-Rate Vocoders (1994)

Recent developments in vector quantization for speech processing

A combined quantization-interpolation scheme for very low bit rate coding of speech LSP parameters

Application of sorted codebook vector quantization to spectral coding of speech

Predictive and mel-scale binary vector quantization of variable dimension spectral magnitude