| Paper: | SLP-P12.1 | ||
| Session: | Speech Processing for Reverberation, Quantization and Enhancement | ||
| Time: | Thursday, May 18, 10:00 - 12:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech and Spoken Language Processing: Speech Enhancement (for Impaired Situations) | ||
| Title: | SPEECH DEREVERBERATION BY COMBINING MINT-BASED BLIND DECONVOLUTION AND MODIFIED SPECTRAL SUBTRACTION | ||
| Authors: | Ken'ichi Furuya, Sumitaka Sakauchi, Akitoshi Kataoka, NTT Corporation, Japan | ||
| Abstract: | A dereverberation technique is developed to provide an alternative means of reducing reverberation in speech signals. The conventional MINT (the multiple-input/output inverse-filtering theorem) method uses the room impulse responses to calculate the inverse filters, so it cannot recover speech signals in practice, where the room impulse responses are unknown in advance. Our method blindly estimates the inverse filters by computing the correlation matrix between input signals that can be observed, instead of room impulse responses. We also combine the inverse filtering with modified spectral subtraction against the estimation error of inverse filters used in the field. The performance of the proposed method is demonstrated using actual room impulse responses. | ||
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