Speaker identification (SI) and speech recognition systems display a strong sensitivity to ambient noise conditions. It is known that the performance of these systems is maximized when trained under conditions that approximate the testing environment. However these systems generally do not perform well when there is no noise or when the level or characteristics of the noise changes. A new speech enhancement technique is presented that, when used with a standard cepstrum-based SI system, significantly reduces the sensitivity of the SI system to mismatches in the noise environment between training and testing.
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