Robust i-vector based adaptation of DNN acoustic model for speech recognition
INTERSPEECH, pp. 2877-2881, 2015.
In the past, conventional i-vectors based on a Universal Background Model (UBM) have been successfully used as input features to adapt a Deep Neural Network (DNN) Acoustic Model (AM) for Automatic Speech Recognition (ASR). In contrast, this paper introduces Hidden Markov Model (HMM) based ivectors that use HMM state alignment information ...More
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