2006 Fiscal Year Final Research Report Summary
Construction of speech acquisition mechanism based on sensory information
| Project/Area Number |
16200015
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Waseda University |
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Principal Investigator |
HONDA Masaaki Waseda University, Faculty of Sport Sciences, Professor, スポーツ科学学術院, 教授 (90367095)
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| Co-Investigator(Kenkyū-buntansha) |
TAKANISHI Atsuo Waseda University, Faculty of Science and Engineering, Professor, 理工学部, 教授 (50179462)
HONDA Kiyoshi Advanced Telecommunications Research Institute International, Department Head, 人間情報科学研究所, 室長 (90395088)
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| Project Period (FY) |
2004 – 2006
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| Keywords | Speech Production / Speech Acquisition / Motor Planning / Robotics / Artificial Vocal Cords / Hidden Markov Model / Sensory Feedback / fMRI |
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| Research Abstract |
We have been studied speech acquisition mechanism based on sensory information in perturbation studies of sensory feedback during speech articulation and constructive studies by using mechanical talking robot mimicking human speech production.
1. Perturbation Study : We investigated sensory feedback effects on speech production by using a perturbation paradigm. The external perturbation was unexpectedly applied on the palatal shape during speech utterance under the masked auditory and tactile feedback conditions. Then, we observed brain activity by using fMRI during the compensatory response by the tongue to the perturbation. We found that the compensatory response was brought by the neural adaptation mechanism in the central nerves system.
2. Talking Robot Study : We have developed an 3 dimensional talking robot (mechanical speech synthesizer) which mimicking human speech production process. This robot has artificial mechanical lung, glottis, tongue, jaw, lips and velum as speech organs
… More
which are dynamically controlled by servo mechanism. The speech sounds are produced by glottal source generated by self-oscillating vocal cords, random source generated by passing the air flow through the narrow constriction in the vocal tract, and time varying vocal tract acoustic resonance. The talking robot is dynamically controlled by feed-forward-feedback mechanism. The control planning is automatically trained for a desired speech acoustics and sensory information like tactile information between the tongue and the palate and oral pressure. We proposed a stochastic speech inversion method for mapping the speech acoustics to the articulatory positions based on Hidden Markov Model. Also, we proposed a planning method based on a Jacobean updating rule to determine the articulatory positions from the sensory information. The larynx control planning is also studied based on forward-inverse neural network model for determining the robot parameters of larynx for a desired acoustics like pitch frequency, voice-unvoiced information, and voice quality. Less
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Research Products
(12 results)
