Semi Supervised and Cross Lingual Knowledge Transfer Learnings for DNN Hybrid Acoustic Models Under Low Resource Conditions
Semi supervised and cross lingual knowledge transfer learnings are two strategies for boosting performance of lowresource speech recognition systems. In this paper, we propose a unified knowledge transfer learning method to deal with these two learning tasks. Such a knowledge transfer learning is realized by fine tuning of Deep Neural Network (DNN) We demonstrate its effectiveness in both monolingual based semisupervised learning task and cross lingual knowledge transfer learning task. We then combine these two learning strategies to obtain further performance improvement.
INTERSPEECH