Abstract | ||
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Speech and voice technologies are experiencing a profound review as new paradigms are sought to overcome some specific problems which cannot be completely solved by classical approaches. Neuromorphic Speech Processing is an emerging area in which research is turning the face to understand the natural neural processing of speech by the Human Auditory System in order to capture the basic mechanisms solving difficult tasks in an efficient way. In the present paper a further step ahead is presented in the approach to mimic basic neural speech processing by simple neuromorphic units standing on previous work to show how formant dynamics - and henceforth consonantal features - can be detected by using a general neuromorphic unit which can mimic the functionality of certain neurons found in the upper auditory pathways. Using these simple building blocks a General Speech Processing Architecture can be synthesized as a layered structure. Results from different simulation stages are provided as well as a discussion on implementation details. Conclusions and future work are oriented to describe the functionality to be covered in the next research steps. |
Year | DOI | Venue |
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2011 | 10.1016/j.neucom.2010.07.023 | Neurocomputing |
Keywords | Field | DocType |
neuromorphic computing,speech processing | Speech processing,Auditory pathways,Architecture,Neural processing,Computer science,Neuromorphic engineering,Speech recognition,Artificial intelligence,Formant,Neurocomputational speech processing,Human auditory system,Machine learning | Journal |
Volume | Issue | ISSN |
74 | 8 | 0925-2312 |
Citations | PageRank | References |
6 | 0.79 | 5 |
Authors | ||
7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Pedro Gómez Vilda | 1 | 289 | 52.48 |
José Manuel Ferrández De Vicente | 2 | 42 | 11.19 |
María Victoria Rodellar Biarge | 3 | 44 | 13.67 |
Agustín Álvarez Marquina | 4 | 65 | 11.29 |
Luis Miguel Mazaira-Fernández | 5 | 57 | 9.66 |
Rafael Martínez-Olalla | 6 | 72 | 11.95 |
Cristina Muñoz-Mulas | 7 | 23 | 5.72 |