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Separating speaker and environmental variability using factored transforms
Two primary sources of variability that degrade accuracy in speech recognition systems are the speaker and the environment. While many algorithms for speaker or environment adaptation have been proposed to improve performance, far less attention has been paid to approaches which address for both factors. In this paper, we present a method for compensating for speaker and environmental mismatch using a cascade of CMLLR transforms. The proposed approach enables speaker transforms estimated in onedoi:10.21437/interspeech.2011-415 fatcat:qwahi2t365bf7cifkda5ddef2y