An Optimal Set of Flesh Points on Tongue and Lips for Speech-Movement Classification
An Optimal Set of Flesh Points on Tongue and Lips for Speech-Movement Classification
复制标题
DOI：
10.1044/2015_jslhr-s-14-0112
复制
发表时间：
2016-02-01
影响因子：
2.6
通讯作者：
Green, Jordan R.
中科院分区：
文献类型：
--
作者：
Wang, Jun;Samal, Ashok;Green, Jordan R.
用途：作者试图确定一个最佳的一组肉点上的舌头和嘴唇的语音movements.Method分类：作者使用电磁articulographs（Carstens AG 500和NDI波）记录舌头和嘴唇的动作，从13个健康的谈话者谁清楚8个元音，11个辅音，一组语音平衡的话，和一组简短的短语在录音。我们使用了机器学习分类器（支持向量机）的发音运动的基础上对语音刺激进行分类。然后，我们比较了肉点组合的分类精度，以确定一组最佳的传感器。（T1：舌尖与舌叶之间的距离; T4：舌体后部; UL：上唇; LL：下唇）相结合，音素和单词分类最准确，并且与完整集合具有可比性结论：我们确定了一个4传感器集，即T1，T4，UL，LL，产生了一个分类准确率（91%-95%）等同于使用所有6个传感器。这些研究结果提供了一个经验基础，选择传感器和它们的位置的科学和新兴的临床应用，结合发音运动。
Purpose: The authors sought to determine an optimal set of flesh points on the tongue and lips for classifying speech movements.Method: The authors used electromagnetic articulographs (Carstens AG500 and NDI Wave) to record tongue and lip movements from 13 healthy talkers who articulated 8 vowels, 11 consonants, a phonetically balanced set of words, and a set of short phrases during the recording. We used a machine-learning classifier (support-vector machine) to classify the speech stimuli on the basis of articulatory movements. We then compared classification accuracies of the flesh-point combinations to determine an optimal set of sensors.Results: When data from the 4 sensors (T1: the vicinity between the tongue tip and tongue blade; T4: the tongue-body back; UL: the upper lip; and LL: the lower lip) were combined, phoneme and word classifications were most accurate and were comparable with the full set (including T2: the tongue-body front; and T3: the tongue-body front).Conclusion: We identified a 4-sensor set-that is, T1, T4, UL, LL-that yielded a classification accuracy (91%-95%) equivalent to that using all 6 sensors. These findings provide an empirical basis for selecting sensors and their locations for scientific and emerging clinical applications that incorporate articulatory movements.