12.1 Background of Deep Learning在线视频

语音信号数字处理课程列表：

1. Introduction

-1.1 Outline

--1.1 Outline

--图文单元

-1.2 Application of digital speech signal processing

--1.2 Application of digital speech signal processing

-1.3 Development history of speech signal processing

--1.3 Development history of speech signal processing

-1.4 Basic Knowledge of speech signal

--1.4 Basic Knowledge of speech signal

-Test

--Test

2. Fundamentals of Speech processing

-2.1 Speech processing techniques

--2.1 Speech processing techniques

-2.2 Short-time analysis and windowing

--2.2 Short-time analysis and windowing

-2.3 Short-time parameters of speech signal

--2.3 Short-time parameters of speech signal

-2.4 Pitch estimation

--2.4 Pitch estimation

-Test

--Test

3. Speech production and perception

-3.1 Speech chain

--3.1 Speech chain

-3.2 Speech production

--Speech production

-3.3 Speech perception

--3.3 Speech perception

-3.4 Speech quality test

--3.4 Speech quality test

-Test

--Test

4. Linear predictive analysis（LPA）

-4.1 Basic concepts of LP

--4.1 Basic concepts of LP

-4.2 Estimation of LP coefficients

--4.2 Estimation of LP coefficients

-4.3 LP spectrum and basic features

--4.3 LP spectrum and basic features

-4.4 Alternative Representations of LP parameters

--4.4 Alternative Representations of LP parameters

-Test

--Test

5. Homomorphic analysis（HA）

-5.1 Homomorphic systems

--5.1 Homomorphic systems

-5.2 Cepstrum and complex cepstrum

--5.2 Cepstrum and complex cepstrum

-5.3 Homomorphic filtering

--5.3 Homomorphic filtering

-5.4 Homomorphic analysis of speech signal

--5.4 Homomorphic analysis of speech signal

-Test

--Test

6. Vector quantization（VQ）

-6.1 Basic concept of VQ

--6.1 Basic concept of VQ

-6.2 VQ system design

--6.2 VQ system design

-6.3 Codebook design algorithms

--6.3 Codebook design algorithm

-6.4 Different types of VQ

--6.4 Different types of VQ

-Test

--Test

7. Hidden Markov Models（HMM）

-7.1 Prerequisite knowledge

--7.1 Prerequisite knowledge

-7.2 Basic concept of HMM

--7.2 Basic concept of HMM

-7.3 Three basic problems of HMM

--7.3 Three basic problems of HMM

-7.4 Insights of HMM

--7.4 Insights of HMM

-Test

--Test

8. Speech Coding

-8.1 Overview of speech coding

--8.1 Overview of speech coding

-8.2 Speech coding strategies

--8.2 Speech coding strategies

-8.3 Code Excited Linear Prediction (CELP)

--8.3 Code Excited Linear Prediction (CELP)

-8.4 Key technologies of speech coding

--8.4 Key technologies of speech coding

-Test

--Test

9. Speech Recognition

-9.1 Overview of speech recognition

--9.1 Overview of speech recognition

-9.2 Basic speech recognition systems

--9.2 Basic speech recognition systems

-9.3 Models in speech recognition

--9.3 Models in speech recognition

-9.4 Challenges for speech recognition

--9.4 Challenges for speech recognition

-Test

--Test

10. Speech Enhancement

-10.1 Overview of speech enhancement

--10.1 Overview of speech enhancement

-10.2 Speech separation problem

--10.2 Speech separation problem

-10.3 Monaural speech denoising

--10.3 Monaural speech denoising

-10.4 Other speech enhancement techniques

--10.4 Other speech enhancement techniques

-Test

--Test

11. Speech Synthesis

-11.1 Overview of speech synthesis

--11.1 Overview of speech synthesis

-11.2 Methods of speech synthesis(PartI)

--11.2 Methods of speech synthesis(PartI)

-11.3 Methods of speech synthesis(PartII)

--11.3 Methods of speech synthesis(PartII)

-11.4 Prosody and PSOLA

--11.4 Prosody and PSOLA

-Test

--Test

12. Latest development in speech signal processing

-12.1 Background of Deep Learning

--12.1 Background of Deep Learning

-12.2 Outline of neural networks

--12.2 Outline of neural networks

-12.3 Deep learning based speech recognition

--12.3 Deep learning based speech recognition

-12.4 Deep learning based speech separation

--12.4 Deep learning based speech separation

-Test

--Test

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