| Paper: | SLP-P2.1 | ||
| Session: | Speech Production, Analysis and Modeling | ||
| Time: | Tuesday, May 16, 10:30 - 12:30 | ||
| Presentation: | Poster | ||
| Topic: | Speech and Spoken Language Processing: Speech Production | ||
| Title: | Learning Electropalatograms from Acoustics | ||
| Authors: | Asterios Toutios, Konstantinos Margaritis, University of Macedonia, Greece | ||
| Abstract: | Electropalatography is a well established technique for recording information on the patterns of contact between the tongue and the hard palate during speech, leading to a stream of binary vectors called electropalatograms, consisting of elecropalatographic events - contacts or non-contacts between the tongue and the palate. A data-driven approach to mapping the speech signal onto electropalatographic information is presented. A combination of Principal Component Analysis and Support Vector Regression is used, yielding classification scores of more than 93% on individual electropalatographic events, for a single speaker. This may be viewed as a special case of the, well-known in the speech community, speech inversion problem which refers to inferring production parameters from the speech signal. | ||
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