We present a framework for speech recognition that accounts for hidden articulatory information. We model the articulatory space using a codebook of articulatory configurations g...
We present an approach to detecting and recognizing spoken isolated phrases based solely on visual input. We adopt an architecture that first employs discriminative detection of ...
Kate Saenko, Karen Livescu, Michael Siracusa, Kevi...
Visual information has been shown to improve the performance of speech recognition systems in noisy acoustic environments. However, most audio-visual speech recognizers rely on a ...
Although gesture recognition has been studied extensively, communicative, affective, and biometrical “utility” of natural gesticulation remains relatively unexplored. One of t...
In this work a Gaussian Hidden Markov Model (GHMM) based automatic sign language recognition system is built on the SIGNUM database. The system is trained on appearance-based feat...