Comparison Studies of Several Microphone Robustness Techniques
| dc.contributor.author | Sonmez, M.K. | en_US |
| dc.contributor.author | Kao, Yu-Hung | en_US |
| dc.contributor.author | Rajasekaran, P.K. | en_US |
| dc.contributor.author | Baras, John S. | en_US |
| dc.contributor.department | ISR | en_US |
| dc.date.accessioned | 2007-05-23T09:56:31Z | |
| dc.date.available | 2007-05-23T09:56:31Z | |
| dc.date.issued | 1994 | en_US |
| dc.description.abstract | We study the effectiveness of various microphone robustness techniques from the viewpoint of speech recognition, utilizing the ARPA-sponsored Wall Street Journal (WSJ) data base [1]. Two of the techniques considered are being introduced in this paper: two cepstral normalization algorithms utilizing the artificial neural network techniques Self Organizing Map (SOM) and Learning Vector Quantization (LVQ). The algorithms obtained are low- complexity non-parametric counterparts of the parametric approaches Codeword-dependent Cepstral Normalization (CDCN) and Fixed CDCN (FCDCN). The other techniques considered are Cepstral Mean Normalization (CMN), RASTA, SNR-dependent Cepstral Normalization (SDCN), Interpolated SDCN (ISDCN), CDCN, FCDCN; some of these techniques require one or more of the following information: stereo data, SNR estimate, single microphone data for adaptation, and knowledge of the microphone used for the specific data under test. We determine the effectiveness in several ways: (i) scattergram plot of the speech frame parameter vector (usually a cepstral vector), (ii) adjusted deviation ratio, measured from scattergram, and (iii) correctness of classifying a test vector into a vector code book. All these measures have direct correlation with speech recognition performance, which will be measured with experiments to be conducted. | en_US |
| dc.format.extent | 238638 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1903/5509 | |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | ISR; TR 1994-30 | en_US |
| dc.subject | neural systems | en_US |
| dc.subject | robust information processing | en_US |
| dc.subject | speech processing | en_US |
| dc.subject | Systems Integration | en_US |
| dc.title | Comparison Studies of Several Microphone Robustness Techniques | en_US |
| dc.type | Technical Report | en_US |
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