Tibetan Language Speech Recognition Model Based on Active Learning and Semi-Supervised Learning

In the researches on Tibetan language speech recognition, accurate labeling of Tibetan speech utterances is extremely time consuming and requires trained linguists. For alleviate this problem, we present an approach that can use few labeled Tibetan speech utterances to construct the effective recognition model. The experimental results show that our approach has better performance than traditional methods based on semi-supervised learning and supervised learning.