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The JD AI Speaker Verification System for the FFSVC 2020 Challenge
Ying Tong
, Wei Xue
, Shanluo Huang
, Lu Fan
, Chao Zhang
, Guohong Ding
, Xiaodong He
Department of Computer Science
Research output
:
Chapter in book/report/conference proceeding
›
Conference proceeding
›
peer-review
7
Citations (Scopus)
Overview
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Dive into the research topics of 'The JD AI Speaker Verification System for the FFSVC 2020 Challenge'. Together they form a unique fingerprint.
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Keyphrases
Speaker Recognition System
100%
AI Speaker
100%
Far-field Speaker Verification
100%
Verification Challenges
100%
Beamforming
50%
Mandarin
25%
Training Data
25%
Training Set
25%
Fusion Method
25%
Factorized
25%
U-Net
25%
Channel Switching
25%
Far-field Data
25%
Delayed Neural Networks
25%
Multiple Methods
25%
Output Value
25%
Equal Error Rate
25%
Microphone Array
25%
Self-attentive
25%
Text-independent Speaker Verification
25%
Field Text
25%
Two-level Fusion
25%
Voice Channels
25%
Weighted Prediction Error
25%
Single Microphone
25%
Statistical Pooling
25%
Speaker Characteristics
25%
Network Transformers
25%
Detection Cost Function
25%
Engineering
Artificial Intelligence
100%
Beamforming
100%
Prediction Error
50%
Field Data
50%
Model Structure
50%
Delay Time
50%
Cost Function
50%
Output Value
50%
Equal Error Rate
50%
Microphone Array
50%
Text Field
50%
Final Result
50%
Resnet
50%
Computer Science
Artificial Intelligence
100%
Verification System
100%
Speaker Verification
100%
Training Data
16%
Prediction Error
16%
Multiple Method
16%
time-delay
16%
Structure Model
16%
Residual Neural Network
16%
Preprocessing
16%
Equal Error Rate
16%
Open Access
16%
Transformer Neural Network
16%