Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Critical Analysis of Speech Recognition of Tamil and Malay Language Through Artificial Neural Network

Version 1 : Received: 4 February 2021 / Approved: 5 February 2021 / Online: 5 February 2021 (10:58:40 CET)

How to cite: Pal Thamburaj, K.; Ponniah, K.; Sivanathan, I.; Kumar, M. An Critical Analysis of Speech Recognition of Tamil and Malay Language Through Artificial Neural Network. Preprints 2021, 2021020156 (doi: 10.20944/preprints202102.0156.v1). Pal Thamburaj, K.; Ponniah, K.; Sivanathan, I.; Kumar, M. An Critical Analysis of Speech Recognition of Tamil and Malay Language Through Artificial Neural Network. Preprints 2021, 2021020156 (doi: 10.20944/preprints202102.0156.v1).

Abstract

Human and Computer interaction has been a part of our day-to-day life. Speech is one of the essential and comfortable ways of interacting through devices as well as a human being. The device, particularly smartphones have multiple sensors in camera and microphone, etc. speech recognition is the process of converting the acoustic signal to a smartphone as a set of words. The efficient performance of the speech recognition system highly enhances the interaction between humans and machines by making the latter more receptive to user needs. The recognized words can be applied for many applications such as Commands & Control, Data entry, and Document preparation. This research paper highlights speech recognition through ANN (Artificial Neural Network). Also, a hybrid model is proposed for audio-visual speech recognition of the Tamil and Malay language through SOM (Self-organizing map0 and MLP (Multilayer Perceptron). The Effectiveness of the different models of NN (Neural Network) utilized in speech recognition will be examined.

Subject Areas

ANN; NN; Speech Recognition; interaction; hybrid method

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