模糊评价系统:智能语音评价系统

A. Zourmand, T. Nong
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引用次数: 0

摘要

本研究展示马来语元音智能语音评估系统的模糊评价方法设计。建议的系统确实适合儿童患者可以进行评估。目标客户是7至12岁的马来儿童。将隐马尔可夫模型作为语音识别技术应用于系统中。客户可以在自己方便的时间独立练习和测试,系统可以对他们的发音和发音质量进行评估。模糊评价环节可以对每个客户的元音发音表现进行反馈。为了得到准确的评价,模糊专家决策系统采用三个参数作为输入。形成峰频率的距离、HMM的对数概率和HMM正确识别的次数是影响语音质量的主要因素,并参与系统的决策过程。工程结果表明,所提出的模糊专家评价系统的准确率提高了89%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy Evaluation System: Intelligent Speech Assessment System
This research shows the design of a fuzzy evaluation approach in an intelligent speech assessment system for Malay vowels. The suggested system is really suitable for the children patient can undertake assessment. The target client is 7 to 12 years Malay children. Hidden Markov Model is applied as a technique of speech recognition in the system. Clients are able to exercise and test on their own convenience time independently and the system is able to evaluate their pronunciation as well as the quality of their pronunciation. The fuzzy evaluation session can provide a feedback on the performance of each client vowel pronunciation. In order to have an accurate evaluation, three parameters are involved in fuzzy expert decision making system as inputs. The distance of the formant frequencies, log-probability of HMM and number of correct recognition by HMM play the main rule in vowel quality uttered by client which involved in decision making process of the proposed system. The result of project shows that, the accuracy of the proposed fuzzy expert evaluation system increase up to 89%.
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