Computer Science
Mel-Frequency Cepstral Coefficients
100%
Filtering Method
62%
Spectral Envelope
59%
Speech Waveform
56%
Vocal Tract Filter
56%
Speaker Recognition
37%
Generative Adversarial Networks
37%
Open Environment
37%
Dynamic Programming
37%
Waveform Generator
37%
Flow Model
37%
Use Case
37%
Vector Quantization
37%
Mel Frequency Cepstral Coefficient
37%
Human Speech Production
37%
Feature Extraction
37%
Acoustic Feature
37%
Synthesis Technique
37%
Velocity Signal
37%
Common Platform
37%
Coding Efficiency
34%
Speech Synthesis
31%
Recognition System
28%
Model Architecture
18%
Text To Speech
18%
Deep Neural Network
18%
Sparsity
18%
State Space
18%
Tracking Method
18%
Training Data
18%
Estimation Accuracy
18%
Excitation Signal
12%
Voice Signal
12%
Assessment Objective
12%
Automatic Detection
12%
Support Vector Machine
12%
Speech Application
12%
Detection Performance
12%
Fundamental Frequency
12%
Neural Network
12%
Systematic Analysis
12%
Statistical Mapping
9%
Recognition Performance
9%
Experimental Result
9%
Coding Performance
9%
Scalar Quantization
9%
Priori Information
9%
Joint Distribution
9%
Gaussian Mixture Model
9%
Engineering
Speech Signal
62%
Fundamental Frequency
56%
Speech Waveform
56%
Pathology Detection
37%
Test Time
37%
Filterbank
37%
Acoustic Feature
37%
Phase Analysis
37%
Vector Quantization
37%
Recurrent
37%
Pressure Signal
37%
Physical Modeling
25%
Nonlinear System
18%
Dynamic Programming
18%
Source Spectrum
18%
Limited Resource
18%
System Behavior
18%
Acoustic Field
18%
Time Domain
18%
Flow Model
12%
Test Data
12%
Test Signal
12%
Filtering Algorithm
12%
Synthesis Filter
12%
Main Part
12%
Multichannel
12%
Initial Set
9%
Time Analysis
9%
Joint Distribution
9%
Coding Efficiency
9%
Excitation Source
9%
Sparsity
9%
Scalar Quantization
9%
Experimental Result
9%
Priori Information
9%
Deep Neural Network
9%
Gaussian Mixture Model
9%
Main Disadvantage
9%
Central Part
9%
Source Information
6%