Abstract
As a child acquires language, he or she: perceives acoustic information in his or her surrounding environment; identifies portions of the ambient acoustic information as language-related; and associates that language-related information with his or her perception of his or her own language-related acoustic productions. The present work models the third task. We use a semisupervised alignment algorithm based on manifold learning. We discuss the concepts behind this approach, and the application of the algorithm to this task. We present experimental evidence indicating the usefulness of manifold alignment in learning speaker normalization.
Original language | English (US) |
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Pages | 2918-2921 |
Number of pages | 4 |
State | Published - Dec 1 2010 |
Event | 11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010 - Makuhari, Chiba, Japan Duration: Sep 26 2010 → Sep 30 2010 |
Other
Other | 11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010 |
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Country/Territory | Japan |
City | Makuhari, Chiba |
Period | 9/26/10 → 9/30/10 |
Keywords
- Language acquisition
- Manifold alignment
- Speaker normalization