Where Should Pitch Accents and Phrase Breaks Go? A Syntax Tree Transducer Solution

Motivated by a desire to assess the prosody of foreign language learners, this study demonstrates the benefit of highlevel syntactic information in automatically deciding where phrase breaks and pitch accents should go in text. The connection between syntax and prosody is well-established, and naturally lends itself to tree-based probabilistic models. With automatically-derived parse trees paired to tree transducer models, we found that categorical prosody tags for unseen text can be determined with significantly higher accuracy than they can with a baseline method that uses n-gram models of part-ofspeech tags. On the Boston University Radio News Corpus, the tree transducer outperformed the baseline by 14% overall for accents, and by 3% overall for breaks. These automatic results fell within this corpus’s range of inter-speaker agreement in assigning accents and breaks to text.