Analysis and recognition of accentual patterns

This study proposes a framework of automatic analysis and recognition of accentual 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 accentual 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 accentual patterns of utterances using the acoustic-phonetic representation which involves two steps: detection of accentual prominence and assigning pitch accent types to prominent syllables. The efficiency of the best models consists in achieving high accuracy (above 80% on average) using small acoustic feature vectors.