Detection of questions in Chinese conversational speech

What features are helpful for Chinese question detection? Which of them are more important? What are the differences between Chinese and English regarding feature importance? We study these questions by building question detectors for Chinese and English conversational speech, and performing analytic studies and feature selection experiments. As in English, we find that both textual and prosodic features are helpful for Chinese question detection. Among textual features, word identities, especially the utterance-final word, are more useful than the global (N-gram) sentence likelihood. Unlike in English, where final pitch rise is a good cue for questions, we find in Chinese that utterance final pitch behavior is not a good feature. Instead, the most useful prosodic feature is the spectral balance, i.e., the distribution of energy over the frequency spectrum, of the final syllable. We also find effects of tone, e.g., that treating interjection words as having a special tone is helpful. Our final classifier achieves an error rate of 14.9% with respect to a 50% chance-level rate.