Phoneme recognition using visual features on speech spectrograms

In order to apply speech spectrogram reading heuristics to an automatic speech recognition system, a more accurate expression of the heuristics must be developed. In particular, the transformation between acoustic feature measurements and phoneme candidates must be developed in a quantitative manner. In this paper, a visual acoustic-feature labeland a phoneme identification approach using this label is proposed. The visual acoustic-feature label, which is a polygon on a speech spectrogram, represents some aspects of an acoustic feature by its own geometric characteristics. Preliminary experimental results show that phoneme identification using the visual acoustic-feature label is feasible for realizing the quantitative transformation rules between the acoustic feature measurements and phoneme candidates.