Weakly Supervised Training for Parsing Mandarin Broadcast Transcripts


W. Wang, “Weakly supervised training for parsing Mandarin broadcast transcripts,” in Proc. 9th Annual Conference of the International Speech Communication Association 2008 (INTERSPEECH 2008), pp. 2446–2449.


We present a systematic investigation of applying weakly supervised co-training approaches to improve parsing performance for parsing Mandarin broadcast news (BN) and broadcast conversation (BC) transcripts, by iteratively retraining two competitive Chinese parsers from a small set of treebanked data and a large set of unlabeled data. We compare co-training to self-training, and our results show that performance using co-training is significantly better than with self-training and both co-training and self-training with a small seed labeled corpus can improve parsing accuracy significantly over training on the mismatching newswire treebank.

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