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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
Pages4438-4443
Number of pages6
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe
Duration: 2009 May 122009 May 17

Other

Other2009 IEEE International Conference on Robotics and Automation, ICRA '09
CityKobe
Period09/5/1209/5/17

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ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Kanda, H., Ogata, T., Takahashi, T., Komatani, K., & Okuno, H. G. (2009). Continuous vocal imitation with self-organized vowel spaces in recurrent neural network. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 4438-4443). [5152818] https://doi.org/10.1109/ROBOT.2009.5152818