Digital speech coding for low bit rate communication systems
Building on the success of the first edition Digital Speech offers extensive new, updated and revised material based upon the latest research. This Second Edition continues to provide the fundamental technical background required for low bit rate speech coding and the hottest developments in digital...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Chichester :
Wiley
c2004.
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| Edición: | 2nd ed |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627054706719 |
Tabla de Contenidos:
- Digital Speech; Contents; Preface; Acknowledgements; 1 Introduction; 2 Coding Strategies and Standards; 2.1 Introduction; 2.2 Speech Coding Techniques; 2.2.1 Parametric Coders; 2.2.2 Waveform-approximating Coders; 2.2.3 Hybrid Coding of Speech; 2.3 Algorithm Objectives and Requirements; 2.3.1 Quality and Capacity; 2.3.2 Coding Delay; 2.3.3 Channel and Background Noise Robustness; 2.3.4 Complexity and Cost; 2.3.5 Tandem Connection and Transcoding; 2.3.6 Voiceband Data Handling; 2.4 Standard Speech Coders; 2.4.1 ITU-T Speech Coding Standard; 2.4.2 European Digital Cellular Telephony Standards
- 2.4.3 North American Digital Cellular Telephony Standards2.4.4 Secure Communication Telephony; 2.4.5 Satellite Telephony; 2.4.6 Selection of a Speech Coder; 2.5 Summary; Bibliography; 3 Sampling and Quantization; 3.1 Introduction; 3.2 Sampling; 3.3 Scalar Quantization; 3.3.1 Quantization Error; 3.3.2 Uniform Quantizer; 3.3.3 Optimum Quantizer; 3.3.4 Logarithmic Quantizer; 3.3.5 Adaptive Quantizer; 3.3.6 Differential Quantizer; 3.4 Vector Quantization; 3.4.1 Distortion Measures; 3.4.2 Codebook Design; 3.4.3 Codebook Types; 3.4.4 Training, Testing and Codebook Robustness; 3.5 Summary
- Bibliography4 Speech Signal Analysis and Modelling; 4.1 Introduction; 4.2 Short-Time Spectral Analysis; 4.2.1 Role of Windows; 4.3 Linear Predictive Modelling of Speech Signals; 4.3.1 Source Filter Model of Speech Production; 4.3.2 Solutions to LPC Analysis; 4.3.3 Practical Implementation of the LPC Analysis; 4.4 Pitch Prediction; 4.4.1 Periodicity in Speech Signals; 4.4.2 Pitch Predictor (Filter) Formulation; 4.5 Summary; Bibliography; 5 Efficient LPC Quantization Methods; 5.1 Introduction; 5.2 Alternative Representation of LPC; 5.3 LPC to LSF Transformation; 5.3.1 Complex Root Method
- 5.3.2 Real Root Method5.3.3 Ratio Filter Method; 5.3.4 Chebyshev Series Method; 5.3.5 Adaptive Sequential LMS Method; 5.4 LSF to LPC Transformation; 5.4.1 Direct Expansion Method; 5.4.2 LPC Synthesis Filter Method; 5.5 Properties of LSFs; 5.6 LSF Quantization; 5.6.1 Distortion Measures; 5.6.2 Spectral Distortion; 5.6.3 Average Spectral Distortion and Outliers; 5.6.4 MSE Weighting Techniques; 5.7 Codebook Structures; 5.7.1 Split Vector Quantization; 5.7.2 Multi-Stage Vector Quantization; 5.7.3 Search strategies for MSVQ; 5.7.4 MSVQ Codebook Training; 5.8 MSVQ Performance Analysis
- 5.8.1 Codebook Structures5.8.2 Search Techniques; 5.8.3 Perceptual Weighting Techniques; 5.9 Inter-frame Correlation; 5.9.1 LSF Prediction; 5.9.2 Prediction Order; 5.9.3 Prediction Factor Estimation; 5.9.4 Performance Evaluation of MA Prediction; 5.9.5 Joint Quantization of LSFs; 5.9.6 Use of MA Prediction in Joint Quantization; 5.10 Improved LSF Estimation Through Anti-Aliasing Filtering; 5.10.1 LSF Extraction; 5.10.2 Advantages of Low-pass Filtering in Moving Average Prediction; 5.11 Summary; Bibliography; 6 Pitch Estimation and Voiced-Unvoiced Classification of Speech; 6.1 Introduction
- 6.2 Pitch Estimation Methods
