Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System
An improved self-organizing map (SOM), parameterless-growing-SOM (PL-G-SOM), is proposed in this paper. To overcome problems existed in traditional SOM (Kohonen, 1982), kinds of structure-growing-SOMs or parameter-adjusting-SOMs have been invented and usually separately. Here, we combine the idea of...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2010-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2010/307293 |
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| _version_ | 1832545398624878592 |
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| author | Takashi Kuremoto Takahito Komoto Kunikazu Kobayashi Masanao Obayashi |
| author_facet | Takashi Kuremoto Takahito Komoto Kunikazu Kobayashi Masanao Obayashi |
| author_sort | Takashi Kuremoto |
| collection | DOAJ |
| description | An improved self-organizing map (SOM), parameterless-growing-SOM (PL-G-SOM), is proposed in this paper. To overcome problems existed in traditional SOM (Kohonen, 1982), kinds of structure-growing-SOMs or parameter-adjusting-SOMs have been invented and usually separately. Here, we combine the idea of growing SOMs (Bauer and Villmann, 1997; Dittenbach et al. 2000) and a parameterless SOM (Berglund and Sitte, 2006) together to be a novel SOM named PL-G-SOM to realize additional learning, optimal neighborhood preservation, and automatic tuning of parameters. The improved SOM is applied to construct a voice instruction learning system for partner robots adopting a simple reinforcement learning algorithm. User's instructions of voices are classified by the PL-G-SOM at first, then robots choose an expected action according to a stochastic policy. The policy is adjusted by the reward/punishment given by the user of the robot. A feeling map is also designed to express learning degrees of voice instructions. Learning and additional learning experiments used instructions in multiple languages including Japanese, English, Chinese, and Malaysian confirmed the effectiveness of our proposed system. |
| format | Article |
| id | doaj-art-c31d70482e7a4059aca98f11573b70ac |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2010-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-c31d70482e7a4059aca98f11573b70ac2025-02-03T07:26:00ZengWileyJournal of Robotics1687-96001687-96192010-01-01201010.1155/2010/307293307293Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning SystemTakashi Kuremoto0Takahito Komoto1Kunikazu Kobayashi2Masanao Obayashi3Graduate School of Science and Engineering, Yamaguchi University, Tokiwadai 2-16-1, Ube, Yamaguchi 755-8611, JapanGraduate School of Science and Engineering, Yamaguchi University, Tokiwadai 2-16-1, Ube, Yamaguchi 755-8611, JapanGraduate School of Science and Engineering, Yamaguchi University, Tokiwadai 2-16-1, Ube, Yamaguchi 755-8611, JapanGraduate School of Science and Engineering, Yamaguchi University, Tokiwadai 2-16-1, Ube, Yamaguchi 755-8611, JapanAn improved self-organizing map (SOM), parameterless-growing-SOM (PL-G-SOM), is proposed in this paper. To overcome problems existed in traditional SOM (Kohonen, 1982), kinds of structure-growing-SOMs or parameter-adjusting-SOMs have been invented and usually separately. Here, we combine the idea of growing SOMs (Bauer and Villmann, 1997; Dittenbach et al. 2000) and a parameterless SOM (Berglund and Sitte, 2006) together to be a novel SOM named PL-G-SOM to realize additional learning, optimal neighborhood preservation, and automatic tuning of parameters. The improved SOM is applied to construct a voice instruction learning system for partner robots adopting a simple reinforcement learning algorithm. User's instructions of voices are classified by the PL-G-SOM at first, then robots choose an expected action according to a stochastic policy. The policy is adjusted by the reward/punishment given by the user of the robot. A feeling map is also designed to express learning degrees of voice instructions. Learning and additional learning experiments used instructions in multiple languages including Japanese, English, Chinese, and Malaysian confirmed the effectiveness of our proposed system.http://dx.doi.org/10.1155/2010/307293 |
| spellingShingle | Takashi Kuremoto Takahito Komoto Kunikazu Kobayashi Masanao Obayashi Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System Journal of Robotics |
| title | Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System |
| title_full | Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System |
| title_fullStr | Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System |
| title_full_unstemmed | Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System |
| title_short | Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System |
| title_sort | parameterless growing som and its application to a voice instruction learning system |
| url | http://dx.doi.org/10.1155/2010/307293 |
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