Continuous vocal imitation with self-organized vowel spaces in recurrent neural network

Hisashi Kanda*, Tetsuya Ogata, Toru Takahashi, Kazunori Komatani, Hiroshi G. Okuno

*この研究の対応する著者

研究成果: Conference contribution

11 被引用数 (Scopus)

抄録

A continuous vocal imitation system was developed using a computational model that explains the process of phoneme acquisition by infants. Human infants perceive speech sounds not as discrete phoneme sequences but as continuous acoustic signals. One of critical problems in phoneme acquisition is the design for segmenting these continuous speech sounds. The key idea to solve this problem is that articulatory mechanisms such as the vocal tract help human beings to perceive speech sound units corresponding to phonemes. To segment acoustic signal with articulatory movement, we apply the segmenting method to our system by Recurrent Neural Network with Parametric Bias (RNNPB). This method determines the multiple segmentation boundaries in a temporal sequence using the prediction error of the RNNPB model, and the PB values obtained by the method can be encoded as kind of phonemes. Our system was implemented by using a physical vocal tract model, called the Maeda model. Experimental results demonstrated that our system can self-organize the same phonemes in different continuous sounds, and can imitate vocal sound involving arbitrary numbers of vowels using the vowel space in the RNNPB. This suggests that our model reflects theprocess of phoneme acquisition.

本文言語English
ホスト出版物のタイトル2009 IEEE International Conference on Robotics and Automation, ICRA '09
ページ4438-4443
ページ数6
DOI
出版ステータスPublished - 2009 11月 2
外部発表はい
イベント2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe, Japan
継続期間: 2009 5月 122009 5月 17

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
ISSN(印刷版)1050-4729

Conference

Conference2009 IEEE International Conference on Robotics and Automation, ICRA '09
国/地域Japan
CityKobe
Period09/5/1209/5/17

ASJC Scopus subject areas

  • ソフトウェア
  • 制御およびシステム工学
  • 人工知能
  • 電子工学および電気工学

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