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Full-Text Articles in Medicine and Health Sciences
Across-Speaker Articulatory Normalization For Speaker-Independent Silent Speech Recognition, Jun Wang, Ashok Samal, Jordan Green
Across-Speaker Articulatory Normalization For Speaker-Independent Silent Speech Recognition, Jun Wang, Ashok Samal, Jordan Green
CSE Conference and Workshop Papers
Silent speech interfaces (SSIs), which recognize speech from articulatory information (i.e., without using audio information), have the potential to enable persons with laryngectomy or a neurological disease to produce synthesized speech with a natural sounding voice using their tongue and lips. Current approaches to SSIs have largely relied on speaker-dependent recognition models to minimize the negative effects of talker variation on recognition accuracy. Speaker-independent approaches are needed to reduce the large amount of training data required from each user; only limited articulatory samples are often available for persons with moderate to severe speech impairments, due to the logistic difficulty of …
Preliminary Test Of A Real-Time, Interactive Silent Speech Interface Based On Electromagnetic Articulograph, Jun Wang, Ashok Samal, Jordan R. Green
Preliminary Test Of A Real-Time, Interactive Silent Speech Interface Based On Electromagnetic Articulograph, Jun Wang, Ashok Samal, Jordan R. Green
CSE Conference and Workshop Papers
A silent speech interface (SSI) maps articulatory movement data to speech output. Although still in experimental stages, silent speech interfaces hold significant potential for facilitating oral communication in persons after laryngectomy or with other severe voice impairments. Despite the recent efforts on silent speech recognition algorithm development using offline data analysis, online test of SSIs have rarely been conducted. In this paper, we present a preliminary, online test of a real-time, interactive SSI based on electromagnetic motion tracking. The SSI played back synthesized speech sounds in response to the user’s tongue and lip movements. Three English talkers participated in this …
Word Recognition From Continuous Articulatory Movement Time-Series Data Using Symbolic Representations, Jun Wang, Arvind Balasubramanian, Luis Mojica De La Vega, Jordan R. Green, Ashok Samal, Balakrishnan Prabhakaran
Word Recognition From Continuous Articulatory Movement Time-Series Data Using Symbolic Representations, Jun Wang, Arvind Balasubramanian, Luis Mojica De La Vega, Jordan R. Green, Ashok Samal, Balakrishnan Prabhakaran
CSE Conference and Workshop Papers
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 …
Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi
Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi
CSE Conference and Workshop Papers
Data mining of protein databases poses special challenges because many protein databases are non- relational whereas most data mining and machine learning algorithms assume the input data to be a type of rela- tional database that is also representable as an ARFF file. We developed a method to restructure protein databases so that they become amenable for various data mining and machine learning tools. Our restructuring method en- abled us to apply both decision tree and support vector machine classifiers to a pancreatic protein database. The SVM classifier that used both GO term and PFAM families to characterize proteins gave …