Bird Song Synthesis Based on Hidden Markov Models

Jordi Bonada, Robert Lachlan, Merlijn Blaauw


This paper focuses on the synthesis of bird songs using Hidden Markov Models (HMM). This technique has been widely used for speech modeling and synthesis. However, features and contextual factors typically used for human speech are not appropriate for modeling bird songs. Moreover, while for speech we can easily control the content of the recordings, this is not the case for bird songs, where we have to rely on the spontaneous singing of the animal. In this work we briefly overview the characteristics of bird songs, compare them to speech, and propose strategies for adapting the widely-used HTS (HMM-based Speech Synthesis System) framework to model and synthesize bird songs. In particular, we focus on Chaffinch species and a database of recordings of several song bouts of one male bird. At the end we discuss the synthesis results obtained.


DOI: 10.21437/Interspeech.2016-1110

Cite as

Bonada, J., Lachlan, R., Blaauw, M. (2016) Bird Song Synthesis Based on Hidden Markov Models. Proc. Interspeech 2016, 2582-2586.

Bibtex
@inproceedings{Bonada+2016,
author={Jordi Bonada and Robert Lachlan and Merlijn Blaauw},
title={Bird Song Synthesis Based on Hidden Markov Models},
year=2016,
booktitle={Interspeech 2016},
doi={10.21437/Interspeech.2016-1110},
url={http://dx.doi.org/10.21437/Interspeech.2016-1110},
pages={2582--2586}
}