NDLI: Unsupervised noise model estimation for model-based robust speech recognition

Content Provider	IEEE Xplore Digital Library
Author	Graciarena, M. Franco, H.
Copyright Year	2003
Description	Author affiliation: Speech Technol. & Res. Lab., SRI Int., USA (Graciarena, M.; Franco, H.)
Abstract	Within the framework of a generalization of Rose's integrated parametric model (IPM) to the Gaussian mixture hidden Markov model (HMM) formulation to model speech in noisy environments, we further extend an algorithm for the maximum likelihood (ML) estimation of the noise HMM component. We propose: (1) a gain normalization algorithm in the log filterbank domain, which uses a gain estimate that is less degraded in broadband noise conditions; (2) the use of an augmented feature to incorporate dynamic information, which enables the use of the same probability density computation as the instantaneous feature; and (3) a technique for unsupervised noise model estimation using a phone loop grammar, which does not require an initial recognition pass. This algorithm does not require speech/nonspeech detection. In noisy digit recognition experiments, using HTK and NOISEX-92 databases, the noise estimation algorithm achieves, in supervised and unsupervised cases, performance similar to using noise models trained with the noise source data only.
Starting Page	351
Ending Page	356
File Size	403242
Page Count	6
File Format	PDF
ISBN	0780379802
DOI	10.1109/ASRU.2003.1318466
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-11-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise robustness Speech recognition Hidden Markov models Working environment noise Gaussian noise Maximum likelihood estimation Parametric statistics Speech enhancement Maximum likelihood detection Filter bank
Content Type	Text
Resource Type	Article

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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
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