Bird song synthesis based on hidden Markov models

Abstract

Comunicació presentada a l'Interspeech 2016, celebrat els dies 8 a 12 de setembre de 2016 a San Francisco, California.

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.