Adaptation of deep neural network acoustic models using factorised i-vectors

  title={Adaptation of deep neural network acoustic models using factorised i-vectors},
  author={Panagiota Karanasou and Yongqiang Wang and Mark J. F. Gales and Philip C. Woodland},
The use of deep neural networks (DNNs) in a hybrid configuration is becoming increasingly popular and successful for speech recognition. One issue with these systems is how to efficiently adapt them to reflect an individual speaker or noise condition. Recently speaker i-vectors have been successfully used as an additional input feature for unsupervised speaker adaptation. In this work the use of i-vectors for adaptation is extended to incorporate acoustic factorisation. In particular, separate… CONTINUE READING
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