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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yamakawa, K. Kikuchi, H. Matsui, T. Itahashi, S. |
| Copyright Year | 2009 |
| Description | Author affiliation: Waseda University, Japan (Kikuchi, H.) || National Institute of Informatics, Japan (Yamakawa, K.; Itahashi, S.) || The Institute of Statistical Mathematics, Japan (Matsui, T.) |
| Abstract | The purpose of this study is to visualize the similarities among multiple speech corpora. In order for users to easily utilize various speech corpora, we reported a visualization method based on the corpus attribute using MDS. We had proposed the eight attributes as the speech corpus features. However, these attributes contained no acoustical feature of the speech corpus. The acoustical feature is important information in some intended use of corpus. In this paper, we propose a new attribute, the acoustical feature of speech corpora, in addition to the conventional attributes. The results of visualization indicates that the method using the new attribute can visualize better the similarities between multiple speech corpora. This will facilitate searching efficiently the specific corpus that fits a user's needs. Based on the obtained results, we built a corpus search system which corpus users can use as a benchmark of corpus selection. The outline and possibility of this system are described. |
| Starting Page | 143 |
| Ending Page | 147 |
| File Size | 1309770 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424444007 |
| DOI | 10.1109/ICSDA.2009.5278359 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-10 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Loudspeakers Speech analysis Acoustic noise Natural languages Data visualization Speech recognition Mathematics Application software Speech processing Microphones |
| Content Type | Text |
| Resource Type | Article |
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