以音韻屬性偵測擷取對話語音關鍵詞之研究 (Study on Keyword Spotting using Prosodic Attribute Detection for Conversational Speech) [In Chinese]

It is one of most essential issues to extract the keywords from conversational speech for understanding the utterances from speakers. This thesis aims at keyword spotting from spontaneous speech for keyword detecting. We proposed prosodic features that are used for keyword detection. The prosody words are segmented from speaker’s utterance according to the pre-training decision tree. The supported vector machine is further used as the classifier to judge the prosody word is keyword or not. The prosody word boundary segmentation algorithm based on decision tree is illustrated. Besides the data driven feature, the knowledge obtained from the corpus observation is integrated in the decision tree. Finally, the keyword Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012)