Extending AuToBI to prominence detection in European Portuguese

Helena Moniz, Ana Isabel Mata, Julia Hirschberg, Fernando Batista, Andrew Rosenberg, Isabel Trancoso


This paper describes our exploratory work in applying the Automatic ToBI annotation system (AuToBI), originally developed for Standard American English, to European Portuguese. This work is motivated by the current availability of large amounts of (highly spontaneous) transcribed data and the need to further enrich those transcripts with prosodic information. Manual prosodic annotation, however, is al- most impractical for extensive data sets. For that reason, automatic systems such as AuToBi stand as an alternate solution. We have started by applying the AuToBI prosodic event detection system using the existing English models to the prediction of prominent prosodic events (accents) in European Portuguese. This approach achieved an overall accuracy of 74% for prominence detection, similar to state-of-the-art results for other languages. Later, we have trained new models using prepared and spontaneous Portuguese data, achieving a considerable improvement of about 6% accuracy (absolute) over the existing English models. The achieved results are quite encouraging and provide a starting point for automatically predicting prominent events in European Portuguese.


 DOI: 10.21437/SpeechProsody.2014-43

Cite as: Moniz, H., Mata, A.I., Hirschberg, J., Batista, F., Rosenberg, A., Trancoso, I. (2014) Extending AuToBI to prominence detection in European Portuguese. Proc. 7th International Conference on Speech Prosody 2014, 280-284, DOI: 10.21437/SpeechProsody.2014-43.


@inproceedings{Moniz2014,
  author={Helena Moniz and Ana Isabel Mata and Julia Hirschberg and Fernando Batista and Andrew Rosenberg and Isabel Trancoso},
  title={{Extending AuToBI to prominence detection in European Portuguese}},
  year=2014,
  booktitle={Proc. 7th International Conference on Speech Prosody 2014},
  pages={280--284},
  doi={10.21437/SpeechProsody.2014-43},
  url={http://dx.doi.org/10.21437/SpeechProsody.2014-43}
}