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Spontaneous conversations are an integral element in many CSCW environments. Although speech is often regarded as the most natural and effective way of communication between human beings, speech data are not efficient for quick review. One solution to help people access speech data efficiently in CSCW environments is to conduct speech summarization. Up till now, most speech summarization research has focused on broadcast news; nevertheless summarizing spontaneous conversations is more valuable for CSCW. The task is also more challenging, for example, spontaneous conversations often contain more speech disfluencies, which need to be coped with properly; they are also more vulnerable to speech recognition errors. This demonstration is built to show the prototype of our summarization system. Compared with previous work, our summarizer addresses the problem further in several important respects. First, the system summarizes spontaneous conversations with a wide variety of information/features that have not been explored before, which improve summarization performance according to our experiments. Second, our summarizer handles speech disfluencies, which in all previous work was either not explicitly handled or removed as noise.
Zhu et al. (Sun,) studied this question.