Deep Learning Convolutional Neural Network for Speech Recognition: A Review
Kazheen Ismael Taher & Adnan Mohsin Abdulazeez
In the last few decades, there has been considerable amount of research on the use of Machine Learning (ML) for speech recognition based on Convolutional Neural Network (CNN). These studies are generally focused on using CNN for applications related to speech recognition. Additionally, various works are discussed that are based on deep learning since its emergence in the speech recognition applications. Comparing to other approaches, the approaches based on deep learning are showing rather interesting outcomes in several applications including speech recognition, and therefore, it attracts a lot of researches and studies. In this paper, a review is presented on the developments that occurred in this field while also discussing the current researches that are being based on the topic currently.
Keywords: Machine Learning, Speech Recognition, Convolutional Neural Networks, Deep Learning, Word Error Rate (WER).
|Title:||Deep Learning Convolutional Neural Network for Speech Recognition: A Review|
|Author:||Kazheen Ismael Taher & Adnan Mohsin Abdulazeez|
|Journal Name:||International Journal of Science and Business|
|ISSN:||ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)|
|Date of Publication:||28/01/2021|
|Paper Type:||Literature Review|
Cite This Article:
Kazheen Ismael Taher & Adnan Mohsin Abdulazeez (2021). Deep Learning Convolutional Neural Network for Speech Recognition: A Review. International Journal of Science and Business, 5(3), 1-14. doi: https://doi.org/10.5281/zenodo.4475361
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About Author (s)
Kazheen Ismael Taher (corresponding author), Information Technology Department, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: firstname.lastname@example.org
Professor Adnan Mohsin Abdulazeez, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: email@example.com