Corpus and transcription system of Chinese Lecture Room
Sheng Li, Yuya Akita, Tatsuya Kawahara · 2014
The paper introduces our project on automatic speech recognition (ASR) of Chinese lectures. For a comprehensive study on spontaneous Chinese, we compile a corpus of Chinese Lecture Room (CCLR), which has faithful transcripts and caption texts. Based on the annotated alignment of these texts, we conduct analysis on linguistic phenomena of spontaneous Chinese speech. We also develop a baseline ASR system with this corpus, and refine it with the DNN-HMM framework. By exploiting the lecture data without faithful transcripts and conducting unsupervised speaker adaptation, significant improvement of ASR accuracy is achieved.