Study of Speech Recognition Using CNN
At a glance
- Citations
- 30
- References
- 23
- Comments
- 0
Abstract
Artificial Neural Networks is one of the most preferable topics in Machine Learning. Various applications like Google Assistant, Google Translator, Apple Siri, etc are implemented on these Artificial Neural Networks. All these applications are based on Speech Recognition. Nowadays Speech Recognition plays a prominent role in many fields, the machine can recognize words and sentences in spoken language and translate them into machine-readable formats. Different methods of speech recognition include Hidden Markov Model (HMM), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), etc. The main objective of this paper is to know how MFCC is helpful in the recognition of speech commands spoken by the speakers using Convolutional Neural Networks. Convolutional neural networks help train the machine to recognize the spoken words by using Speech Recognition.
Publication details
- DOI
- 10.1109/icais53314.2022.9743083
- OpenAlex
- W4221130810
- Document type
- conference-paper
- Language
- EN
- Source
- 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS)
- Last metadata update
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