2771-1463ISSN (Online)
2771-1471ISSN (Print)
Volume 5 , Issue 2 , PP: 08-14, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
C. Vivek 1 * , M. Indu 2 , N. Nandhini 3
Doi: https://doi.org/10.54216/JCHCI.050201
Speech is a verbal communication used by humans through language. Likewise speech recognition is a process of converting speech to text. This paper provides a study of use of artificial neural networks(ANN) in speech recognition. Hidden Markov models (HMM) is a traditional statistical techniques for performing speech recognition. In speech detection software, Mel frequency cepstral coefficients (MFCCs) are frequently used. With different approaches evolving, we deal with the features used to recognize the speech pattern and implementation of speech recognition in the efficient types of artificial neural network (ANN).
Artificial neural network, Signals , , Artificial Neuron , Speech Recognition, Feature Extraction , Hidden layers , Artificial Intelligence, Hidden Markov Model(HMM),Mel Frequency Cepstrum Coefficients(MFCC).
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