Characterization of spectral transitions with applications to acoustic sub-word segmentation and automatic speech recognition

A mathematical model has been developed for tracking spectral transitions within the spectral envelope of a speech signal. This technique incorporates linguistic knowledge into a mathematical framework to determine time-varying acoustic-phonetic features and describe formant transitions. The proposed model is quite robust and is capable of extracting not only rapid spectral movement, but also smoother spectral transitions that occur in vowel and sonorant sequences. This basic approach has been previously used to extract steady-state acoustic-phonetic features across spectrally homogeneous regions and to perform speaker dependent recognition in which quite successful results were attained in clean as well as noisy speech. It has now been augmented to capture the dynamics of spectral acoustic-phonetic features.<
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