Speech Prosody 2006

Dresden, Germany
May 2-5, 2006

Unsupervised Learning of Tone and Pitch Accent

Gina-Anne Levow

Department of Computer Science, University of Chicago, IL, USA

Recognition of tone and intonation is essential for speech recognition and language understanding. However, most approaches to this recognition task have relied upon extensive collections of manually tagged data obtained at substantial time and financial cost. In this paper, we explore unsupervised clustering approaches to recognize pitch accent in English and tones in Mandarin Chinese. In unsupervised Mandarin tone clustering experiments, we achieve 57-87% accuracy on materials ranging from broadcast news to clean lab speech. For English pitch accent in broadcast news materials, results reach 78%. These results indicate that the intrinsic structure of tone and pitch accent acoustics can be exploited to reduce the need for costly labeled training data for tone learning and recognition.

Full Paper

Bibliographic reference.  Levow, Gina-Anne (2006): "Unsupervised learning of tone and pitch accent", In SP-2006, paper 224.