抄録
We propose an automatic utterance type recognizer that distinguishes declarative questions from statements in Indonesian speech. Since utterances in these two types have the same words with the same order and differ only in their intonations, their classification requires not only a speech recognizer, but also an intonation recognizer. In this paper, the most important utterance part for distinguishing those two types is first identified by perceptual experiments. Then, an utterance type recognizer using that part is proposed, where polynomial expansion is used as a feature extractor and a neural network is used as a classifier. We evaluated our method using Indonesian speech database including 29 pairs of sentences of those two types, each of which uttered by 35 speakers. It was proved that final word and final-two-syllables are equally effective for the discrimination of each utterance. The proposed recognizer achieved the best accuracy of 89.1% when the order of polynomial expansion was three and the neural network was a linear perceptron.
