.png){kind=icon}
.png){kind=icon}
Return
Deep Speaker Recognition: Process, Progress, and Challenges
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2021.3090109.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Speaker recognition
Speech recognition
Deep learning
Training
Tools
Taxonomy
Biometrics (access control)
Speech processing
speaker recognition
deep learning
end-to-end architectures
meta learning
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W