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An Unsupervised Deep Domain Adaptation Approach For Robust Speech Recognition PDF PDF

12 Pages·2019·English
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by ['Kadek Maydayanti']| 2019| 12 pages| English

About An Unsupervised Deep Domain Adaptation Approach For Robust Speech Recognition PDF

This paper proposes an unsupervised deep domain adaptation (DDA) approach for robust speech recognition. The approach uses a multi-task deep neural network with two classifiers: a label predictor for predicting phonemes and a domain classifier for distinguishing between source and target domains. During training, the network minimizes label loss and maximizes domain loss to learn domain-invariant features. The approach requires only labeled source data and unlabeled target data. Experiments show the approach reduces word error rates by 37.8% on noisy speech compared to a model trained only on clean data.

Detailed Information

Author:['Kadek Maydayanti']
Publication Year:2019
Pages:12
Language:English
Format:PDF
Price:FREE
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