Co-training Approach for Label-Minimized Audio Classification
Wei Zhang, Qun Chao Zhao, Yayu Liu, Minhui Pang · 2010
Audio classification is an important preprocess to the audio data. However, lots of manual labeled data are needed for training models. In order to solve this problem, we evaluate a semi-supervised machine learning algorithm called co-training for content-based audio classification. The audio is divided into there classes: pure speech, pure music and speech mixed with music. We consider the audio features as views and minimize the labeled data quantity by using co-training algorithm. The experimental results on the VOA Special English show the effectiveness of the co-training algorithm for audio classification.