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首页> 外文期刊>Medical and Biological Engineering and Computing: Journal of the International Federation for Medical and Biological Engineering >Genetic algorithm for the efficient selection of disyllabic word lists used in Mandarin speech discrimination tests.
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Genetic algorithm for the efficient selection of disyllabic word lists used in Mandarin speech discrimination tests.

机译：遗传算法用于普通话语音识别测试中有效选择双音节单词列表。

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摘要

Speech audiometric tests have been widely used for advanced hearing diagnoses and in rehabilitation. However, there are no standardised speech tests for more than 90% of the world's population, who do not speak English. A major problem in the design of a speech audiometric test is that the selection of test materials is subject to multiple criteria, and its complexity rises dramatically as the structure of test items changes from phonemic or monosyllabic forms to disyllabic or polysyllabic forms. A genetic algorithm is presented that can automatically select a set of disyllabic words from a large Mandarin corpus. The selection accords with the following principal criteria for the items constituting a speech discrimination test: similarity in structure, familiarity to the subjects, and a phonemically balanced composition. The performance of the genetic algorithm was evaluated by computation of the distance between a target vector, specifying the desired distribution of initial and final syllables and tone patterns for daily disyllabic word usage, and the vector derived by the search results of the algorithm. The use of the genetic algorithm was illustrated by its application to the selection of test lists from two Mandarin corpora. The results showed that, for a given corpus, at least 12 disyllabic word lists with a distance of less than 20 could be generated within 72 h. The genetic algorithm performed an efficient, robust and low-complexity search of the problem space and can be easily modified to adapt to the material selection of other languages.
机译：语音测听测试已广泛用于高级听力诊断和康复中。但是，对于不讲英语的世界上超过90％的人口，没有标准化的语音测试。语音测听测试设计中的一个主要问题是测试材料的选择要遵循多个标准，并且随着测试项目的结构从音位或单音节形式变为双音节或多音节形式，其复杂性急剧上升。提出了一种遗传算法，可以从大型普通话语料库中自动选择一组复音单词。对于构成语音辨别力测试的项目，选择符合以下主要标准：结构相似，对受试者的熟悉程度以及音素均衡的组成。遗传算法的性能通过计算目标向量之间的距离，指定初始和最终音节的期望分布以及日常双音节单词用法的音调模式以及通过算法搜索结果得出的向量来评估。遗传算法在从两个普通话语料库中选择测试清单中的应用说明了遗传算法的使用。结果表明，对于给定的语料库，在72 h内可以生成至少12个距离小于20的复音词列表。遗传算法对问题空间进行了有效，鲁棒和低复杂度的搜索，可以轻松修改以适应其他语言的材料选择。

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