Acoustic-phonetic features for the automatic classification of stop consonants
نویسندگان
چکیده
منابع مشابه
Acoustic-phonetic features for the automatic classification of stop consonants
In this paper, the acoustic–phonetic characteristics of American English stop consonants are investigated. Features studied in the literature are evaluated for their information content and new features are proposed. A statistically guided, knowledge-based, acoustic–phonetic system for the automatic classification of stops, in speaker independent continuous speech, is proposed. The system uses ...
متن کاملAutomatic Detection and Classification of Stop Consonants Using an Acoustic-phonetic Feature-based System
A new acoustic-phonetic feature-and knowledge-based approach for the detection and classification of stop consonants in speakerindependent continuous speech is proposed. A system is built which automatically extracts stop consonants from continuous speech. The detected stop consonants are then passed to the classification system, which classifies them according to their voicing and place of art...
متن کاملThe voicing feature for stop consonants: acoustic phonetic analyses and automatic speech recognition experiments
We examine the distinctive feature [voice] that separates the voiced from the unvoiced sounds for the case of stop consonants. We conduct acoustic-phonetic analyses on a large database and demonstrate the superior separability using a temporal measure (voice onset time; VOT) rather than spectral measures. We describe several algorithms to estimate the VOT automatically from continuous speech an...
متن کاملAn acoustic-phonetic feature-based system for the automatic recognition of fricative consonants
In this paper, the acoustic-phonetic characteristics and the automatic recognition of the American English fricatives are investigated. The acoustic features that exist in the literature are evaluated and new features are proposed. To test the value of the extracted features, a knowledge-based acoustic-phonetic system for the automatic recognition of fricatives, in speaker independent continuou...
متن کاملSegregation of stop consonants from acoustic interference
Speech segregation from acoustic interference is a very challenging task. Previous systems have dealt with voiced speech with success, but they cannot handle unvoiced speech. We study the segregation of stop consonants, which contain significant unvoiced signals. We propose a novel method that employs onset as a major cue to segregate stop consonants. Our system first detects stops through onse...
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ژورنال
عنوان ژورنال: IEEE Transactions on Speech and Audio Processing
سال: 2001
ISSN: 1063-6676
DOI: 10.1109/89.966086