Acoustic‐phonetic features for the automatic recognition of stop consonants

Despite the recent successes in the field of automatic speech recognition, more research is still needed in order to understand the variability of speech and the acoustic characteristics of speech sounds in different contexts and for different speakers. In this paper, the acoustic‐phonetic characteristics and the automatic recognition of the American English stop consonants 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 stops, in speaker independent continuous speech, is proposed. The system uses an auditory‐based front‐end processing and incorporates new algorithms for the extraction and manipulation of the acoustic‐phonetic features that proved to be rich in their information content. Several features, which describe the burst frequency, formant transitions, relative amplitude, spectral shape, and duration, are combined in the recognition process. Recognition accuracy of 95% for voicing detection and 90% for place of articulation detection are obtained for TIMIT database continuous speech of multiple speakers from different dialect regions. The obtained results are analyzed and compared to previous work. [Work was supported by Catalyst Foundation.]