Phoneme segmentation using spectrogram reading knowledge

A method is presented for phoneme segmentation by an expert system utilizing spectrogram reading strategy and knowledge. The expert system detects phonemes in a spectrogram and determines their boundaries as well as their coarse categories. To simulate a human expert spectrogram reading process, the system performs assumption-based inference with certainty factors, and top-down acoustic feature extraction under phonetic context hypotheses. The system, into which Japanese consonant segmentation knowledge is incorporated, is able to detect about 90% of the phonemes correctly. In particular, the phoneme boundaries detected by the system are as accurate as those detected by human experts. The result is that the phonemes obtained by the expert system can be identified using a stochastic phoneme recognition method