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Low-power automatic speech recognition through a mobile GPU and a Viterbi accelerator

Author
Yazdani, R.; Segura, A.; Arnau, J.; Gonzalez, A.
Type of activity
Journal article
Journal
IEEE micro
Date of publication
2017-04-12
Volume
37
Number
1
First page
22
Last page
29
DOI
https://doi.org/10.1109/MM.2017.15 Open in new window
Repository
http://hdl.handle.net/2117/113152 Open in new window
URL
http://ieeexplore.ieee.org/document/7898353/ Open in new window
Abstract
Automatic speech recognition (ASR) has become a core technology for mobile devices. Delivering real-time and accurate ASR has a huge computational cost, which is challenging to achieve in tightly energy-constrained platforms such as mobile devices. A state-of-the-art ASR pipeline consists of a deep neural network (DNN) that converts the audio signal into phonemes' probabilities, followed by a Viterbi search that uses these probabilities to generate a sequence of words. In this article, the autho...
Citation
Yazdani, R., Segura, A., Arnau, J., Gonzalez, A. Low-power automatic speech recognition through a mobile GPU and a Viterbi accelerator. "IEEE micro", 12 Abril 2017, vol. 37, núm. 1, p. 22-29.
Keywords
Accelerator, Automatic speech recognition, Viterbi search
Group of research
ARCO - Microarchitecture and Compilers

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