Journal article
Feature selection via dynamic programming for text-independent speaker identification
IEEE transactions on acoustics, speech, and signal processing, v 26(5), pp 397-403
Oct 1978
Abstract
Dynamic programming is applied to the selection of feature subsets in text-independent speaker identification. Each feature is long-term averaged in order to reduce its variability to text information. The resulting subset of features shows a lower average identification error in comparison to that of the "knock-out" strategy, the cepstral coefficients, and the PARCOR coefficients.
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Details
- Title
- Feature selection via dynamic programming for text-independent speaker identification
- Creators
- R Cheung - Osram SylvaniaB Eisenstein
- Publication Details
- IEEE transactions on acoustics, speech, and signal processing, v 26(5), pp 397-403
- Publisher
- IEEE
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:A1978FS82500001
- Scopus ID
- 2-s2.0-0018023856
- Other Identifier
- 991019174084804721