NDLI: Phone recognition using Restricted Boltzmann Machines

Content Provider	IEEE Xplore Digital Library
Author	Mohamed, A.-r. Hinton, G.
Copyright Year	2010
Description	Author affiliation: Department of Computer Science, University of Toronto, Canada (Mohamed, A.-r.; Hinton, G.)
Abstract	For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited representational capacity of their hidden states. Conditional Restricted Boltzmann Machines (CRBMs) have recently proved to be very effective for modeling motion capture sequences and this paper investigates the application of this more powerful type of generative model to acoustic modeling. On the standard TIMIT corpus, one type of CRBM outperforms HMMs and is comparable with the best other methods, achieving a phone error rate (PER) of 26.7% on the TIMIT core test set.
Starting Page	4354
Ending Page	4357
File Size	154918
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5495651
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Automatic speech recognition Stochastic processes Smoothing methods Computer science Power generation Acoustic applications Error analysis Acoustic testing Bipartite graph distributed representations phone recognition restricted Boltzmann machines
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

Partly hidden Markov model and its application to speech recognition

Factorial Hidden Restricted Boltzmann Machines for noise robust speech recognition

Revisiting semi-continuous hidden Markov models

A Statistical Acoustic Confusability Metric Between Hidden Markov Models

Text-dependent speaker identification using circular hidden Markov models

Acoustic training system for speaker independent continuous Arabic speech recognition system

Time-inhomogeneous hidden Bernoulli model: An alternative to hidden Markov model for automatic speech recognition

Phone recognition using hidden Markov models

Speaker-dependent speech recognition based on phone-like units models-application to voice dialling

Phone recognition using Restricted Boltzmann Machines

Similar Documents

Partly hidden Markov model and its application to speech recognition

Factorial Hidden Restricted Boltzmann Machines for noise robust speech recognition

Revisiting semi-continuous hidden Markov models

A Statistical Acoustic Confusability Metric Between Hidden Markov Models

Text-dependent speaker identification using circular hidden Markov models

Acoustic training system for speaker independent continuous Arabic speech recognition system

Time-inhomogeneous hidden Bernoulli model: An alternative to hidden Markov model for automatic speech recognition

Phone recognition using hidden Markov models

Speaker-dependent speech recognition based on phone-like units models-application to voice dialling

Phone recognition using Restricted Boltzmann Machines