SpeakerSense: Energy efficient unobtrusive speaker identification on mobile phones

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6696 LNCS, Issue , 2011, Pages 188-205

  Lu, Hong ^a,b   Bernheim Brush, A J ^a   Priyantha, Bodhi ^a   Karlson, Amy K ^a   Liu, Jie ^a  

^a MICROSOFT RESEARCH   (United States)

^b Dartmouth Department of Computer Science_Dartmouth College   (United States)

Author keywords

Continuous audio sensing; energy efficiency; heterogeneous multi processor hardware; mobile phones; speaker identification

Indexed keywords

APPLICATION PROCESSORS; AUTOMATIC SEGMENTATIONS; CHANNEL COMPENSATION; COMPUTATION COSTS; CONTINUOUS AUDIO SENSING; ENERGY EFFICIENT; LIFELOGGING; LOW POWER PROCESSORS; MINIMAL POWER; MULTI-PROCESSOR HARDWARE; PERVASIVE COMPUTING APPLICATIONS; PHONE CALLS; SAMPLING RATES; SPEAKER IDENTIFICATION; SPEAKER MODEL; TRAINING DATA; WINDOW SIZE; TRAINING DATA ACQUISITIONS;

COMPUTER ARCHITECTURE; LOUDSPEAKERS; MOBILE DEVICES; MOBILE PHONES; MULTIPROCESSING SYSTEMS; TELEPHONE; TELEPHONE SETS; UBIQUITOUS COMPUTING; CELLULAR TELEPHONES; DATA ACQUISITION; HARDWARE; SPEECH RECOGNITION;

ENERGY EFFICIENCY;

EID: 79958848076     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21726-5_12     Document Type: Conference Paper

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