Functional Model of Acquisition of Spoken Language Using Categorical Algorithm and Hidden Markov Model
| Project/Area Number |
25330201
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | University of the Ryukyus |
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Principal Investigator |
Takara Tomio 琉球大学, 工学部, 教授 (70163326)
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| Co-Investigator(Kenkyū-buntansha) |
IHA Yasushi 国立沖縄高等専門学校, 教授 (60390564)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 隠れマルコフモデル / クラスタ化 / 言語獲得 / モデル / 音声模倣 / 音声言語 / 獲得 / 模倣 / フォルマント / 音声合成 / 教師なし学習 / 音声言語獲得モデル / 音素獲得 / 知覚的マグネット効果 / フォルマント周波数 / 主成分分析 / 聴取実験 / 音素 / 単語 / 子音 / デルタパラメータ |
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| Outline of Final Research Achievements |
We constructed a computer model simulating a baby which can acquire spoken language by itself. Acquisition of vowels is modeled as a clustering of clear parts of speech. Acquisition of words is modeled as a clustering of the hidden Markov model. Consonants are modeled as the different sound part of two words which has the same vowel sequences. Self-training of speech by a baby is modeled by articulatory parameters and the genetic algorithm. It was shown that we can construct a human acquisition model of spoken language if we use the categorical algorithm and the hidden Markov model.
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Report
(4 results)
Research Products
(8 results)
