Speech Communication Human and Machine
Douglas O'Shaughnessy, 1987

Chapter 1. Introduction

1.1. What Is Speech Communication?

1.2. History of Developments in Speech Communication

1.3. Outline of the Book

1.4. Other Topics

Chapter 2. Review of Mathematics for Speech Processing

2.1. Mathematical Preliminaries

2.2. Signals and Linear Systems

2.3. Frequency Analysis

2.4. Circuits

2.5. Discrete-Time Signals and Systems

2.6. Filters

2.7. Probability and Statistics

2.8. Summary

Chapter 3. Speech Production and Acoustic-Phonetics

3.1. Introduction

3.2. Anatomy and Physiology of Speech Organs

3.3. Articulatory Phonetics

3.4. Acoustic-Phonetics

3.5. Acoustic Theory of Speech Production

3.6. Practical Vocal Tract Models for Speech Analysis and Generation

3.7. Coarticulation

3.8. Prosody (Suprasegmentals)

Chapter 4. Hearing

4.1. Introduction

4.2. Anatomy and Physiology of the Ear

4.3. Sound Perception

4.4. Response of the Ear to Complex Stimuli

4.5. Summary

Chapter 5. Speech Perception

5.1. Introduction

5.2. Perceptually Important Features of Speech Signals

5.3. Models of Speech Perception

5.4. Vowel Perception

5.5. Consonant Perception

5.6. Duration as a Phonemic Cue

5.7. Intonation: Perception of Prosody

5.8. Other Aspects of Speech Perception

5.9. Summary

Chapter 6. Speech Analysis

6.1. Introduction

6.2. Short-Time Speech Analysis

6.3. Time-Domain Parameters

6.4. Frequency-Domain Parameters

6.5. Homomorphic (Cepstral) Analysis

6.6. F0 ("Pitch") Estimation

6.7. Reduction of Information

6.8. Summary

Chapter 7. Coding of Speech Signals

7.1. Introduction

7.2. Quantization

7.3. Speech Redundancies and Quality Measures

7.4. Time-Adaptive Waveform Coding

7.5. Exploiting Properties of the Spectral Envelope

7.6. Exploiting the Periodicity of Voiced Speech

7.7. Exploiting Auditory Limitations

7.8. Spectral (Frequency-Domain) Coders

7.9. Vocoders

7.10. Vector Quantization (VQ)

7.11. Network Considerations

7.12. Hardware Implementation: Integrated Circuits

7.13. Summary

Chapter 8. Linear Predictive Coding

8.1. Introduction

8.2. Basic Principles

8.3. Spectral Estimation via LPC

8.4. Updating the LPC Model Sample by Sample

8.5. Window Considerations

8.6. Equivalent Forms for LPC Coefficients

8.7. Parameter Updating and Transmission

8.8. Modifications to Standard LPC

8.9. Different Excitation Models

8.10. Vector Quantization (VQ)

8.11. Hardware Implementation: Integrated Circuits

8.12. Summary

Chapter 9. Speech Synthesis

9.1. Introduction

9.2. Principles of Speech Synthesis

9.3. Synthesizer Operation

9.4. Speech Synthesis in Other Languages

9.5. Hardware for Speech Synthesis

9.6. Summary

Chapter 10. Speech Recognition

10.1. Introduction

10.2. Basic Pattern Recognition Approach

10.3. Preprocessing

10.4. Parametric Representation

10.5. Similarity and Distance Measures

10.6. Segmentation

10.7. Dynamic Time Warping (DTW)

10.8. Search Reduction

10.9. Networks for Speech Recognition

10.10. Labeling Phones in the Cognitive Approach to ASR

10.11. Using Prosodics to Aid Recognition

10.12. Commercial Systems and Hardware

10.13. Summary

Chapter 11. Speaker Recognition

11.1. Introduction

11.2. Verification vs. Recognition

11.3. Recognition Techniques

11.4. Features that Distinguish Speakers

11.5. System Design

11.6. Speaker Recognition by Humans

11.7. Summary


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