期刊
IEEE ACCESS
卷 9, 期 -, 页码 89619-89643出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3090109
关键词
Speaker recognition; Speech recognition; Deep learning; Training; Tools; Taxonomy; Biometrics (access control); Speech processing; speaker recognition; deep learning; end-to-end architectures; meta learning
Speaker recognition is a technology related to identifying speakers from their speech and is shifting towards state-of-the-art deep learning strategies. There is currently a lack of comprehensive survey in the existing deep speaker recognition technologies, with challenges and future directions still to be investigated.
Speaker recognition is related to human biometrics dealing with the identification of speakers from their speech. Speaker recognition is an active research area and being widely investigated using artificially intelligent mechanisms. Though speaker recognition systems were previously constructed using handcrafted statistical means of machine learning, currently it is being shifted to state-of-the-art deep learning strategies. Further, deep learning being a fast-paced domain, an absence of comprehensive survey is observed in the current deep speaker recognition technologies. In this paper, we focus on deep speaker recognition technologies. The paper particularly introduces a taxonomy, explains the progress, architectural strategies and processes of some distinctive approaches. Further, the manuscript classifies and enlists the currently available datasets and programming tools. Finally, the paper investigates the challenges and future directives of deep speaker recognition technology.
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