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

Kingston Pal Thamburaj; Kartheges Ponniah; Ilangkumaran Sivanathan; Muniisvaran Kumar

doi:10.20944/preprints202102.0156.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

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.

ANN; NN; Speech Recognition; interaction; hybrid method

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

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