DocumentCode :
136300
Title :
Hierarchical automatic speech recognition powered by data infrastructure
Author :
Jagatheesan, Arun ; Jong-Roon Ahnn ; Phan, Thomas ; Singh, Abhishek ; Juhan Lee
Author_Institution :
Samsung Res. America, San Jose, CA, USA
fYear :
2014
fDate :
10-13 Jan. 2014
Firstpage :
1140
Lastpage :
1141
Abstract :
Automatic Speech Recognition (ASR) has evolved remarkably over the years and is expected to become a primary form of input to mobile devices including smartphones and wearables. Most large-scale mobile platforms perform speech recognition in the cloud today. There are both advantages and disadvantages to this Cloud-based ASR (Cloud-ASR) approach. Cloud-ASR approach allows for a context oriented human-computer-interaction using speech rather than a mere speech-to-text translation. A Cloud-ASR also has disadvantages such as interruption of the speech service when there is no access to the Cloud-ASR, and also the energy consumption for radio communications, which can drain a mobile battery sooner. We propose the usage of Hierarchical Speech Recognizer (HSR) as an alternative approach to overcome the shortcomings of the Cloud-ASR approach. In the HSR approach, mobile devices perform “selective speech recognition” by themselves as much as possible without contacting an external cloud-based ASR service. In this demonstration, we show our proof-of-concept HSR along with its feasibility and advantages.
Keywords :
mobile computing; mobile handsets; speech recognition; context oriented human computer interaction; data infrastructure; hierarchical automatic speech recognition; hierarchical speech recognizer; mobile devices; selective speech recognition; speech service; Acoustics; Batteries; Computational modeling; Smart phones; Speech; Speech recognition; Automatic Speech Recognition; Consumer Electronics; Data infrastructure; S-Voice; Smart Phone;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Communications and Networking Conference (CCNC), 2014 IEEE 11th
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4799-2356-4
Type :
conf
DOI :
10.1109/CCNC.2014.6940492
Filename :
6940492
Link To Document :
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