The Speech is most prominent & primary mode of Communication among of human being. The communication among human computer interaction is called human computer interface. Speech has potential of being important mode of interaction with computer .This paper gives an overview of major technological perspective and appreciation of the fundamental progress of speech recognition and also gives overview technique developed in each stage of speech recognition. This paper helps in choosing the technique along with their relative merits & demerits. A comparative study of different technique is done as per stages. This paper is concludes with the decision on feature direction for developing technique in human computer interface system using Marathi Language.

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Automatic Speech Recognition (ASR) by machine is an attractive research topic in signal processing domain and has attracted many researchers to contribute in this area. In recent year, there have been many advances in automatic speech reading system with the inclusion of audio and visual speech features to recognize words under noisy conditions. The objective of audio-visual speech recognition system is to improve recognition accuracy. In this paper we computed visual features using Zernike moments and audio feature using Mel Frequency Cepstral Coefficients (MFCC) on 'vVISWa' (Visual Vocabulary of Independent Standard Words) dataset which contains collection of isolated set of city names of 10 speakers. The visual features were normalized and dimension of features set was reduced by Principal Component Analysis (PCA) in order to recognize the isolated word utterance on PCA space.The performance of recognition of isolated words based on visual only and audio only features results in 63.88% and 100% respectively.

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