Authors
Vincent Vanhoucke, Matthieu Devin, Georg Heigold
Publication date
2013/5/26
Conference
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Pages
7582-7585
Publisher
IEEE
Description
ABSTRACT Deep neural networks have been shown to perform very well as acoustic
models for automatic speech recognition. Compared to Gaussian mixtures however, they
tend to be very expensive computationally, making them challenging to use in real-time
applications. One key advantage of such neural networks is their ability to learn from very
long observation windows going up to 400 ms. Given this very long temporal context, it is
tempting to wonder whether one can run neural networks at a lower frame rate than the ...
Total citations
20132014201520162946
Scholar articles
V Vanhoucke, M Devin, G Heigold - 2013 IEEE International Conference on Acoustics, …, 2013