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Learning to assign lexical stress during reading aloud: Corpus, behavioral, and computational investigations

机译:在朗读期间学习分配词汇压力:语料库,行为和计算研究

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Models of reading aloud have tended to focus on the mapping between graphemes and phonemes in monosyllables. Critical adaptations of these models are required when considering the reading of polysyllables, which constitute over 90% of word types in English. In this paper, we examined one such adaptation - the process of stress assignment in learning to read. We used a triangulation of corpus, behavioral, and computational modeling techniques. A corpus analysis of age-appropriate reading materials for children aged 5-12 years revealed that the beginnings and endings of English bisyllabic words are highly predictive of stress position, but that endings are more reliable cues in texts for older children. Children aged 5-12 years revealed sensitivity to both the beginnings and endings when reading nonwords, but older children relied more on endings for determining stress assignment. A computational model that learned to map orthography onto stress showed the same age-related trajectory as the children when assigning stress to nonwords. These results reflect the gradual process of learning the statistical properties of written input and provide key constraints for adequate models of reading aloud.
机译:大声朗读的模式倾向于集中在单音节中的字素和音素之间的映射。当考虑读多音节时,需要对这些模型进行关键的修改,而多音节占英语单词类型的90%以上。在本文中,我们研究了一种这样的适应-学习阅读中的压力分配过程。我们使用了语料库,行为和计算建模技术的三角剖分。对5-12岁儿童的适合年龄的阅读材料的语料库分析显示,英语双音节单词的开头和结尾可以很好地预测重音位置,但是结尾对于年龄较大的孩子而言是更可靠的线索。 5至12岁的儿童在阅读无言词时对开头和结尾都有敏锐度,但是年龄较大的孩子在确定压力分配时更多地依靠结尾。在将重音分配给非单词时,学会将正字法映射到重音上的计算模型显示出与孩子相同的年龄相关轨迹。这些结果反映了学习书面输入的统计属性的渐进过程,并为适当的大声朗读模型提供了关键约束。

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