Abstract
Eye movements can reflect the brain activities in word recognition and speech planning processes during reading and spontaneous speech comprehension. Most of the previous studies used isolated words alone to investigate the latency time of speech planning. However, it is difficult to explore the mechanism for speech planning in the real situation. In this paper, we used continuous speech to investigate the mechanism of speech planning by means of matching eye movements with the utterances during reading Chinese sentences. The plan units of the reading speech were estimated using the fixation of the eye movements, and the latent times for speech planning were measured for each unit in the reading sentences. It is found that the majority of the planning units was a grammatical word, while most of the four-syllable words were planned as two disyllable units. The latent time of the planning units decreases gradually along the time axis of a sentence. When a sentence consists of two sub-sentences, the decline tendency of the latent time was reset in the boundary between the two sub-sentences. When removing the meaning of the sentence by randomizing the word order, however, the declined tendency of the latent time was disappeared. These phenomena showed that the posterior words of the sentences may save time in semantic comprehension since the preceding words provided more semantic information for posterior ones. We can conclude that the semantic comprehension is an important part for speech planning as well as motor command designs, although comprehension is not an explicit task in the uttering.
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Acknowledgements
The research is supported partially by the National Basic Research Program of China (No. 2013CB329301), and the National Natural Science Foundation of China (No. 61303109). The study is supported partially by JSPS KAKENHI Grant (16K00297).
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Huang, J., Zhou, D., Dang, J. (2018). Investigation of Speech-Planning Mechanism Based on Eye Movement. In: Fang, Q., Dang, J., Perrier, P., Wei, J., Wang, L., Yan, N. (eds) Studies on Speech Production. ISSP 2017. Lecture Notes in Computer Science(), vol 10733. Springer, Cham. https://doi.org/10.1007/978-3-030-00126-1_16
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DOI: https://doi.org/10.1007/978-3-030-00126-1_16
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