Presentation 2008-05-23
MDS-based Visualization Method for Multiple Speech Corpus Features
Kimiko YAMAKAWA, Tomoko MATSUI, Shuichi ITAHASHI,
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Abstract(in English) The purpose of this study is to visualize the similarities between speech corpora. Speech data are indispensable for promoting speech research. A wide variety of speech corpora has recently been developed in many countries. Corpus diversification has given users many choices for corpus selection. In order for users to easily utilize these various corpora, we propose a new feature visualization method based on the corpus attribute. First, we listed eight attributes and 58 items of the speech corpora. Then, We analyzed the speech attributes using a multidimensional scaling method (MDS). The results showed that it is possible to visualize the similarities between multiple speech corpora using the proposed method. We also tested the effectiveness of the proposed method by analyzing six imaginary corpora having some specified attributes. This result will facilitate the idea of being able to search a specific corpus according to a user's needs.
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Keyword(in English) speech corpus / corpus features / visualization of feature space / MDS
Paper # TL2008-7
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Committee TL
Conference Date 2008/5/16(1days)
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Registration To Thought and Language (TL)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) MDS-based Visualization Method for Multiple Speech Corpus Features
Sub Title (in English)
Keyword(1) speech corpus
Keyword(2) corpus features
Keyword(3) visualization of feature space
Keyword(4) MDS
1st Author's Name Kimiko YAMAKAWA
1st Author's Affiliation National Institute of Informatics()
2nd Author's Name Tomoko MATSUI
2nd Author's Affiliation The Institute of Statistical Mathematics
3rd Author's Name Shuichi ITAHASHI
3rd Author's Affiliation National Institute of Informatics:National Institute of Advanced Industrial Science & Technology
Date 2008-05-23
Paper # TL2008-7
Volume (vol) vol.108
Number (no) 50
Page pp.pp.-
#Pages 6
Date of Issue