NDLI: The metamorphic algorithm: a speaker mapping approach to data augmentation

Content Provider	IEEE Xplore Digital Library
Author	Bellegarda, J.R. de Souza, P.V. Nadas, A. Nahamoo, D. Picheny, M.A. Bahl, L.R.
Copyright Year	1993
Abstract	Large vocabulary speaker-dependent speech recognition systems adjust to the acoustic peculiarities of each new speaker based on some enrolment data provided by this speaker. As the amount of data required increases with the sophistication of the underlying acoustic models, the enrolment may get lengthy. To streamline it, it is therefore desirable to make use of previously acquired speech data. The authors describe a data augmentation strategy based on a piecewise linear mapping between the feature space of a new speaker and that of a reference speaker. This speaker-normalizing mapping is used to transform the previously acquired data of the reference speaker onto the space of the new speaker. The performance of the resulting procedure, dubbed the metamorphic algorithm, is illustrated on an isolated utterance speech recognition task with a vocabulary of 20000 words. Results show that the metamorphic algorithm can substantially reduce the word error rate when only a limited amount of enrolment data is available. Alternatively, it leads to a level of performance comparable to that obtained when a much greater amount of enrolment data is required from the new speaker. In addition, it can also be used for tracking spectral evolution over time, thus providing a possible means for robust speaker self-adaptation.<>
Starting Page	413
Ending Page	420
Page Count	8
File Size	1029212
File Format	PDF
ISSN	10636676
Volume Number	2
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-07-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Loudspeakers Hidden Markov models Vocabulary Speech recognition Error analysis Piecewise linear techniques Robustness Natural languages Prototypes Parameter estimation
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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

Robust speaker adaptation using a piecewise linear acoustic mapping

Multonic Markov word models for large vocabulary continuous speech recognition

Fast speaker adaptation: some experiments on different techniques for codebook and HMM parameters estimation

Likelihood decision boundary estimation between HMM pairs in speech recognition

Rapid discriminative acoustic model based on eigenspace mapping for fast speaker adaptation

A speaker adaptation technique using linear regression

Experiments using data augmentation for speaker adaptation

Speaker adaptation using constrained estimation of Gaussian mixtures

Speech recognition using speaker adaptation by system parameter transformation

The metamorphic algorithm: a speaker mapping approach to data augmentation

Similar Documents

Robust speaker adaptation using a piecewise linear acoustic mapping

Multonic Markov word models for large vocabulary continuous speech recognition

Fast speaker adaptation: some experiments on different techniques for codebook and HMM parameters estimation

Likelihood decision boundary estimation between HMM pairs in speech recognition

Rapid discriminative acoustic model based on eigenspace mapping for fast speaker adaptation

A speaker adaptation technique using linear regression

Experiments using data augmentation for speaker adaptation

Speaker adaptation using constrained estimation of Gaussian mixtures

Speech recognition using speaker adaptation by system parameter transformation

The metamorphic algorithm: a speaker mapping approach to data augmentation