Direct classification of all American English phonemes using signals from functional speech motor cortex.

Direct classification of all American English phonemes using signals from functional speech motor cortex.
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DOI:
10.1088/1741-2560/11/3/035015
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发表时间:
2014-06
影响因子:
4
通讯作者:
Slutzky MW
Slutzky MW
中科院分区:
工程技术2区
文献类型:
--
作者:
Mugler EM;Patton JL;Flint RD;Wright ZA;Schuele SU;Rosenow J;Shih JJ;Krusienski DJ;Slutzky MW

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虽然脑机接口(BCI)可以以几种不同的方式用于恢复通信,但通信BCI尚未接近自然人类语音的速度或成功率。皮层电图(ECoG)具有精确的时空分辨率,能够记录分布在广泛的皮层区域上的大脑活动,例如在语音产生期间。在这项研究中,我们调查的话,跨越整个音素的一般美国口音使用ECoG与4名受试者。我们对所有音素进行分类时的准确率高达36%,对单个音素的准确率高达63%。此外,误分类的音素遵循语音学文献中描述的发音组织,有助于整个单词的分类。精确的时间对齐音素开始是分类成功的关键。我们确定了特定的时空特征,有助于分类,这可以指导未来的应用。字识别相当于高达3.0位/秒(33.6字/分钟)的信息传输速率,支持BCI控制的语音清晰度追求。
Although brain-computer interfaces (BCIs) can be used in several different ways to restore communication, communicative BCI has not approached the rate or success of natural human speech. Electrocorticography (ECoG) has precise spatiotemporal resolution that enables recording of brain activity that is distributed over a wide area of cortex, such as during speech production. In this study, we investigated words that span the entire set of phonemes in the General American accent using ECoG with 4 subjects. We classified phonemes with up to 36% accuracy when classifying all phonemes and up to 63% accuracy for a single phoneme. Further, misclassified phonemes follow articulation organization described in phonology literature, aiding classification of whole words. Precise temporal alignment to phoneme onset was crucial for classification success. We identified specific spatiotemporal features that aid classification, which could guide future applications. Word identification was equivalent to information transfer rates as high as 3.0 bits/s (33.6 words/min), supporting pursuit of speech articulation for BCI control.
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