Abstract
This work examines energy trajectory and voice quality measurements, in addition to conventional formant and duration properties, to classify tense and lax vowels in English. Tense and lax vowels are produced with differing articulatory configurations which can be identified by measuring acoustic cues such as energy peak location, energy convexity, open quotient and spectral tilt. An analysis of variance (ANOVA) is conducted, and dialect effects are observed. An overall 85.2% classification rate is obtained using the proposed features on the TIMIT database, resulting in improvement over using only conventional acoustic features. Adding the proposed features to widely used cepstral features also results in improved classification.
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