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A robotic voice simulator and the interactive training for hearing-impaired people.

Sawada H, Kitani M, Hayashi Y - J. Biomed. Biotechnol. (2008)

Bottom Line: In this study, the robot is applied to the training system of speech articulation for the hearing-impaired, because the robot is able to reproduce their vocalization and to teach them how it is to be improved to generate clear speech.The paper briefly introduces the mechanical construction of the robot and how it autonomously acquires the vocalization skill in the auditory feedback learning by listening to human speech.Then the training system is described, together with the evaluation of the speech training by auditory impaired people.

View Article: PubMed Central - PubMed

Affiliation: Department of Intelligent Mechanical Systems Engineering, Faculty of Engineering, Kagawa University, Japan. sawada@eng.kagawa-u.ac.jp

ABSTRACT
A talking and singing robot which adaptively learns the vocalization skill by means of an auditory feedback learning algorithm is being developed. The robot consists of motor-controlled vocal organs such as vocal cords, a vocal tract and a nasal cavity to generate a natural voice imitating a human vocalization. In this study, the robot is applied to the training system of speech articulation for the hearing-impaired, because the robot is able to reproduce their vocalization and to teach them how it is to be improved to generate clear speech. The paper briefly introduces the mechanical construction of the robot and how it autonomously acquires the vocalization skill in the auditory feedback learning by listening to human speech. Then the training system is described, together with the evaluation of the speech training by auditory impaired people.

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Structure of self-organizing neural network.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig2: Structure of self-organizing neural network.

Mentions: In this study, the self-organizing neural network (SONN) was employed forthe adaptive learning of vocalization. Figure 2 shows the structure of the SONNconsisting of two processes, which are an information memory process and aninformation recall process. After the SONN learning, the motor controlparameters are adaptively recalled by the stimuli of sounds to be generated.


A robotic voice simulator and the interactive training for hearing-impaired people.

Sawada H, Kitani M, Hayashi Y - J. Biomed. Biotechnol. (2008)

Structure of self-organizing neural network.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2279150&req=5

fig2: Structure of self-organizing neural network.
Mentions: In this study, the self-organizing neural network (SONN) was employed forthe adaptive learning of vocalization. Figure 2 shows the structure of the SONNconsisting of two processes, which are an information memory process and aninformation recall process. After the SONN learning, the motor controlparameters are adaptively recalled by the stimuli of sounds to be generated.

Bottom Line: In this study, the robot is applied to the training system of speech articulation for the hearing-impaired, because the robot is able to reproduce their vocalization and to teach them how it is to be improved to generate clear speech.The paper briefly introduces the mechanical construction of the robot and how it autonomously acquires the vocalization skill in the auditory feedback learning by listening to human speech.Then the training system is described, together with the evaluation of the speech training by auditory impaired people.

View Article: PubMed Central - PubMed

Affiliation: Department of Intelligent Mechanical Systems Engineering, Faculty of Engineering, Kagawa University, Japan. sawada@eng.kagawa-u.ac.jp

ABSTRACT
A talking and singing robot which adaptively learns the vocalization skill by means of an auditory feedback learning algorithm is being developed. The robot consists of motor-controlled vocal organs such as vocal cords, a vocal tract and a nasal cavity to generate a natural voice imitating a human vocalization. In this study, the robot is applied to the training system of speech articulation for the hearing-impaired, because the robot is able to reproduce their vocalization and to teach them how it is to be improved to generate clear speech. The paper briefly introduces the mechanical construction of the robot and how it autonomously acquires the vocalization skill in the auditory feedback learning by listening to human speech. Then the training system is described, together with the evaluation of the speech training by auditory impaired people.

Show MeSH