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Speaker-Independent Silent Speech Recognition from Flesh-Point Articulatory Movements Using an LSTM Neural Network
Silent speech recognition (SSR) converts non-audio information such as articulatory movements into text. SSR has the potential to enable persons with laryngectomy to communicate through natural spoken expression. Current SSR systems have largely relied on speaker-dependent recognition models. The hi...
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| Publicado no: | IEEE/ACM Trans Audio Speech Lang Process |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6154510/ https://ncbi.nlm.nih.gov/pubmed/30271809 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TASLP.2017.2758999 |
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