Title :
Pervasive speech recognition
Author :
Alewine, Neal ; Ruback, Harvey ; Deligne, Sabine
Abstract :
As mobile computing devices grow smaller and as in-car computing platforms become more common, we must augment traditional methods of human-computer interaction. Although speech interfaces have existed for years, the constrained system resources of pervasive devices, such as limited memory and processing capabilities, present new challenges. We provide an overview of embedded automatic speech recognition (ASR) on the pervasive device and discuss its ability to help us develop pervasive applications that meet today´s marketplace needs. ASR recognizes spoken words and phrases. State-of-the-art ASR uses a phoneme-based approach for speech modeling: it gives each phoneme (or elementary speech sound) in the language under consideration a statistical representation expressing its acoustic properties.
Keywords :
human computer interaction; natural language interfaces; speech processing; speech recognition; speech-based user interfaces; ubiquitous computing; acoustic properties; automatic speecb recognition; constrained system resources; elementary speech sound; embedded automatic speech recognition; human-computer interaction; in-car computing platforms; mobile computing devices; pervasive speech recognition; phoneme-based approach; speech modeling; spoken word recognition; statistical representation; Acoustic measurements; Books; Computational modeling; Decoding; Fluid flow measurement; Hidden Markov models; Loudspeakers; Resource management; Speech recognition; Viterbi algorithm; ASR; automatic speech recognition;
Journal_Title :
Pervasive Computing, IEEE
DOI :
10.1109/MPRV.2004.16