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1
Preliminary Test of a Real-Time, Interactive Silent Speech Interface Based on Electromagnetic Articulograph
In: CSE Conference and Workshop Papers (2014)
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2
Individual articulator's contribution to phoneme production
In: CSE Conference and Workshop Papers (2013)
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3
Word Recognition from Continuous Articulatory Movement Time-Series Data using Symbolic Representations
In: CSE Conference and Workshop Papers (2013)
Abstract: Although still in experimental stage, articulation-based silent speech interfaces may have significant potential for facilitating oral communication in persons with voice and speech problems. An articulation-based silent speech interface converts articulatory movement information to audible words. The complexity of speech production mechanism (e.g., co-articulation) makes the conversion a formidable problem. In this paper, we reported a novel, real-time algorithm for recognizing words from continuous articulatory movements. This approach differed from prior work in that (1) it focused on word-level, rather than phoneme-level; (2) online segmentation and recognition were conducted at the same time; and (3) a symbolic representation (SAX) was used for data reduction in the original articulatory movement time-series. A data set of 5,900 isolated word samples of tongue and lip movements was collected using electromagnetic articulograph from eleven English speakers. The average speaker-dependent recognition accuracy was up to 80.00%, with an average latency of 302 miliseconds for each word prediction. The results demonstrated the effectiveness of our approach and its potential for building a real-time articulation-based silent speech interface for clinical applications. The across-speaker variation of the recognition accuracy was discussed.
Keyword: Communication Sciences and Disorders; Computer Sciences; laryngectomy; SAX; silent speech recognition; Speech and Hearing Science; support vector machine; time-series
URL: https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1228&context=cseconfwork
https://digitalcommons.unl.edu/cseconfwork/229
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4
Articulatory Distinctiveness of Vowels and Consonants: A Data-Driven Approach
In: CSE Journal Articles (2013)
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5
Whole-Word Recognition from Articulatory Movements for Silent Speech Interfaces
In: Special Education and Communication Disorders Faculty Publications (2012)
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6
Sentence recognition from articulatory movements for silent speech interfaces
In: Special Education and Communication Disorders Faculty Publications (2012)
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7
Quantifying Articulatory Distinctiveness of Vowels
In: Special Education and Communication Disorders Faculty Publications (2011)
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8
Vowel Recognition from Articulatory Position Time-Series Data
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9
Vowel Recognition from Articulatory Position Time-Series Data
In: CSE Conference and Workshop Papers (2009)
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10
Vowel Recognition from Articulatory Position Time-Series Data
In: Special Education and Communication Disorders Faculty Publications (2009)
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