| 摘要 |
Reducing mismatch between HMMs trained with clean speech and speech signals recorded under background noise can be approached by distribution adaptation using parallel model combination (PMC). Accurate PMC has no closed-form expression, therefore simplification assumptions must be made in implementation. Under a new log-max assumption, adaptation formula for log-spectral parameters are presented, both for static and dynamic parameters. The system takes the mean vector (<HIL><PDAT>41</BOLD><PDAT>) made up of the static part (<HIL><PDAT>41</BOLD><HIL><PDAT>a</ITALIC><PDAT>) and the dynamic part (<HIL><PDAT>41</BOLD><HIL><PDAT>b</ITALIC><PDAT>) and the noise vector (<HIL><PDAT>43</BOLD><PDAT>) made up of the static part (<HIL><PDAT>43</BOLD><HIL><PDAT>a</ITALIC><PDAT>) and dynamic part (<HIL><PDAT>43</BOLD><HIL><PDAT>b</ITALIC><PDAT>) and applies to a decision circuit (<HIL><PDAT>45</BOLD><PDAT>) to determine if the quiet vector plus the gain of speech produced in noise with respect to clean speech is greater than the noisy mean vector and if so the static part is equal to the gain plus the clean speech vector and the dynamic part is the change in the the quiet speech vector and if not greater than the noise vector then the static part equals the noise vector and the dynamic part is zero.</PTEXT>
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