Title :
Automatic bimodal audiovisual speech recognition: A review
Author :
Kandagal, Amaresh P. ; Udayashankara, V.
Author_Institution :
Dept. of Electron. & Comm. Eng., Sri Siddhartha Inst. of Technol., Tumkur, India
Abstract :
Human computer interaction (HCI) is very crucial in our day-to-day activity. Speech is one of the essential and intuitive ways to interact with machines such as Smartphone, which has multiple sensors as microphone, camera, etc. An efficient performance speech recognition system improves interaction between man and machines by making latter more receptive to user needs. Such system has Automatic speech recognition (ASR) engine, which is facing a unique challenge of accuracy in recognition rate. By integrating acoustic signal feature vectors with the visual features, a more robust audiovisual speech recognition engine (AVSR) could be developed for real environmental scenarios. This paper presents past research and development in the field of ASR and AVSR technologies. It describes key technological perspective and admiration of the fundamental progress in ASR and AVSR. The objective of this review is to summarize and compare some of the well-known methods experimented by previous researchers, and to conclude with direction on future research proficiency in HCI system using ASR and AVSR engine.
Keywords :
audio-visual systems; human computer interaction; speech recognition; ASR; AVSR; HCI system; automatic bimodal audiovisual speech recognition; camera; day-to-day activity; efficient performance speech recognition system; human computer interaction; microphone; smartphone; Feature extraction; Hidden Markov models; Mel frequency cepstral coefficient; Speech; Speech recognition; Visualization; Audiovisual speech recognition; Automatic Speech Recognition; Human Computer Interaction; ambient noise; bimodal; classifiers; features extraction;
Conference_Titel :
Contemporary Computing and Informatics (IC3I), 2014 International Conference on
Conference_Location :
Mysore
DOI :
10.1109/IC3I.2014.7019673