Analysis and Recognition of Pitch Accent Patterns

This study proposes a framework of automatic analysis and recognition of pitch accent patterns. In the first place we present the results of analyses which aimed at identification of acoustic cues signaling prominent syllables and different pitch accent types distinguished at the surface-phonological level. The resulting representation provides a framework of analysis of pitch accent patterns at the acoustic-phonetic level. The representation is compact it consists of 13 acoustic features, has low redundancy – the features can not be derived from one another and wide coverage – it encodes distinctions between perceptually different utterances. Next, we train statistical models to automatically determine pitch accent patterns of utterances using the acoustic-phonetic representation. The efficiency of the best models consists in achieving high accuracy (above 80% on average) using small acoustic feature vectors.