Speech recognition based on the distance calculation between intermediate phonetic code sequences in symbolic domain

This paper proposes a speech recognition method alternative to the conventional sample-based statistical methods which are characterized by the necessity of large amounts of training speech data. To resolve this type of heavy processing, the proposed method employs an intermediate phonetic code system and the calculation of distance between phonetic code sequences in symbolic domain. It realizes high efficiency when compared with direct processing of acoustic correlates, although some deterioration will be expected in recognition scores. We first describe the distance calculation method and present specific procedures for obtaining the intermediate code sequence from input utterances and for spotting words using the calculation of distance in the symbolic domain. Preliminary experiments were examined on isolated word recognition and phrase spotting in continuous speech. Word recognition results indicate that the recognition scores obtained by the proposed method are comparable compared with ordinary phone-HMM-based speech recognition.