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We consider the problem of word boundary detection in spontaneous speech utterances. Acoustic features have been well explored in the literature in the context of word boundary detection; however, in spontaneous speech of Switchboard-I corpus, we found that the accuracy of word boundary detection using acoustic features is poor (F-score ~ 0.63). We propose a new feature - that captures lexical cues...
Performance of statistical n-gram language models depends heavily on the amount of training text material and the degree to which the training text matches the domain of interest. The language modeling community is showing a growing interest in using large collections of text (obtainable, for example, from a diverse set of resources on the Internet) to supplement sparse in-domain resources. However,...
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