NDLI: Phoneme recognition using speech image (spectrogram)

Content Provider	IEEE Xplore Digital Library
Author	Ahmadi, M. Bailey, N.J. Hoyle, B.S.
Copyright Year	1996
Description	Author affiliation: Dept. of Electron. & Electr. Eng., Leeds Univ., UK (Ahmadi, M.)
Abstract	In this paper a novel feature extraction technique based on the two-dimensional DCT (discrete cosine transform) and zigzag scanning of the spectrogram is proposed. This is in contrast to conventional approaches based on single dimension analysis such as LPC, cepstral, or FFT. As a phoneme recognition task, a series of experiments were conducted on the voice stops ('b', 'd', 'g') of the TIMIT database uttered by 630 speakers (male and female). The extracted data form the basis for input patterns for training two types of neural networks, the semi-dynamic network (TDNN), and a static network (MLP). The highest recognition rates of 77.5 and 72.4 percent were recorded for TDNN and MLP respectively. This contrasts with results of 72 percent quoted by Hwang et al. (1992) for the same phonemes spoken by 40 females.
Starting Page	675
Ending Page	677
File Size	293791
Page Count	3
File Format	PDF
ISBN	0780329120
DOI	10.1109/ICSIGP.1996.567353
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-10-18
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image recognition Speech recognition Spectrogram Discrete cosine transforms Cepstral analysis Feature extraction Linear predictive coding Databases Data mining Neural networks
Content Type	Text
Resource Type	Article

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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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