Identifying Speakers Using Deep Learning: A review
Lawchak Fadhil Khalid & Adnan Mohsin Abdulazeez
With the advancement of technology and the increasing demand on smart systems and smart applications that provide a quality-of-life improvement, there has been a surge in the demand of more conscious applications, Machine Learning (ML) is considered one of the driving forces behind implementing these types of applications, and one of its implementations is Speaker Identification (SID). Deep Neural Networks (DNNs) and also Recurrent Neural Networks (RNNs) are two main types of Deep Learning that are being used in the implementation of such applications. Speaker Identification is being utilized more and more on daily basis and is being focused on by the research community as a result of this demand. In this paper, a review will be conducted to some of the most recent researches that were conducted in this area and compare their results while discussing their outcomes.
Keywords: Machine Learning, Speaker Identification, Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks.
|Title:||Identifying Speakers Using Deep Learning: A review|
|Author:||Lawchak Fadhil Khalid & Adnan Mohsin Abdulazeez|
|Journal Name:||International Journal of Science and Business|
|ISSN:||ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)|
|Date of Publication:||30/01/2021|
|Paper Type:||Literature Review|
Cite This Article:
Lawchak Fadhil Khalid & Adnan Mohsin Abdulazeez (2021). Identifying Speakers Using Deep Learning: A review. International Journal of Science and Business, 5(3), 15-26. doi: https://doi.org/10.5281/zenodo.4481596
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About Author (s)
Lawchak Fadhil Khalid (corresponding author), Technical College of Informatics – Akre, Duhok Polytechnic University (DPU), Kurdistan Region, Iraq. Email: firstname.lastname@example.org
Adnan Mohsin Abdulazeez, Duhok Polytechnic University (DPU), Kurdistan Region, Iraq.