Presentation | 2000/12/1 Learning Effect on Perception of Tone Sequences with Noise Masayuki MATSUMOTO, Kazushi MURAKOSHI, Kiyohiko NAKAMURA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This study presents three psychophysical experiments which investigated the effect of learning on the cocktail party effect. 1)Subjects were required to repeatedly listen to a pure tone sequence perceieved as one stream, and the then to say that they could segregate two sequences as two streams, when the repeated sequence and the other sequence were listened to at the same time. It was shown that segregation rate raised as the learning progressed. 2)Subjects were required to listen to a pure tone sequence perceived as one stream repeatedly, and then to detect it from noise. It was shown that the correct rate in the detection raised as the learning progressed. 3)The pure tone sequence was changed so that they could not be perceived as one stream, for instance the interval of the sounds was extended. The correct rate was not raised as the learning prgressed. From these above, it was suggested that the cocktail party effect results from learning, and is caused by perceiving target sounds as one stream. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | cocktail party effect / tone sequence / auditory stream / perceptual learning |
Paper # | NC2000-80 |
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Committee | NC |
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Conference Date | 2000/12/1(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Learning Effect on Perception of Tone Sequences with Noise |
Sub Title (in English) | |
Keyword(1) | cocktail party effect |
Keyword(2) | tone sequence |
Keyword(3) | auditory stream |
Keyword(4) | perceptual learning |
1st Author's Name | Masayuki MATSUMOTO |
1st Author's Affiliation | Dept. Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology() |
2nd Author's Name | Kazushi MURAKOSHI |
2nd Author's Affiliation | Dept. Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology |
3rd Author's Name | Kiyohiko NAKAMURA |
3rd Author's Affiliation | Dept. Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology |
Date | 2000/12/1 |
Paper # | NC2000-80 |
Volume (vol) | vol.100 |
Number (no) | 490 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |