The traditional approach to automatic speech recognition continues to push the limits of its implementation. The multimodal approach to audio-visual speech recognition and its neuromorphic computational modeling is a novel data driven paradigm that will lead towards zero instruction set computing and will enable proactive capabilities in audio-visual recognition systems. An engineeringoriented deployment of the audio-visual processing framework is discussed in this paper, proposing a bimodal speech recognition framework to process speech utterances and lip reading data, applying soft computing paradigms according to a bio-inspired and the holistic modeling of speech.
|Titolo:||Biomorphic Modeling of Phoneme Identification and Classification Based on an Evolving Fuzzy-neural Network : From Hardcomputing to Softcomputing|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||mag-2017|
|Enti collegati al convegno:||IEEE INNS (International Neural Networks Society)|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|