(NOTE: Each chapter begins with an introduction and concludes with a Summary, Exercises and Bibliography.) 1. Introduction. Discrete-Time Speech Signal Processing. The Speech Communication Pathway. Analysis/Synthesis Based on Speech Production and Perception. Applications. Outline of Book. 2. A Discrete-Time Signal Processing Framework. Discrete-Time Signals. Discrete-Time Systems. Discrete-Time Fourier Transform. Uncertainty Principle. z-Transform. LTI Systems in the Frequency Domain. Properties of LTI Systems. Time-Varying Systems. Discrete-Fourier Transform. Conversion of Continuous Signals and Systems to Discrete Time. 3. Production and Classification of Speech Sounds. Anatomy and Physiology of Speech Production. Spectrographic Analysis of Speech. Categorization of Speech Sounds. Prosody: The Melody of Speech. Speech Perception. 4. Acoustics of Speech Production. Physics of Sound. Uniform Tube Model. A Discrete-Time Model Based on Tube Concatenation. Vocal Fold/Vocal Tract Interaction. 5. Analysis and Synthesis of Pole-Zero Speech Models. Time-Dependent Processing. All-Pole Modeling of Deterministic Signals. Linear Prediction Analysis of Stochastic Speech Sounds. Criterion of "Goodness". Synthesis Based on All-Pole Modeling. Pole-Zero Estimation. Decomposition of the Glottal Flow Derivative. Appendix 5.A: Properties of Stochastic Processes. Random Processes. Ensemble Averages. Stationary Random Process. Time Averages. Power Density Spectrum. Appendix 5.B: Derivation of the Lattice Filter in Linear Prediction Analysis. 6. Homomorphic Signal Processing. Concept. Homomorphic Systems for Convolution. Complex Cepstrum of Speech-Like Sequences. Spectral Root Homomorphic Filtering. Short-Time Homomorphic Analysis of Periodic Sequences. Short-Time Speech Analysis. Analysis/Synthesis Structures. Contrasting Linear Prediction and Homomorphic Filtering. 7. Short-Time Fourier Transform Analysis and Synthesis. Short-Time Analysis. Short-Time Synthesis. Short-Time Fourier Transform Magnitude. Signal Estimation from the Modified STFT or STFTM. Time-Scale Modification and Enhancement of Speech. Appendix 7.A: FBS Method with Multiplicative Modification. 8. Filter-Bank Analysis/Synthesis. Revisiting the FBS Method. Phase Vocoder. Phase Coherence in the Phase Vocoder. Constant-Q Analysis/Synthesis. Auditory Modeling. 9. Sinusoidal Analysis/Synthesis. Sinusoidal Speech Model. Estimation of Sinewave Parameters. Synthesis. Source/Filter Phase Model. Additive Deterministic-Stochastic Model. Appendix 9.A: Derivation of the Sinewave Model. Appendix 9.B: Derivation of Optimal Cubic Phase Parameters. 10. Frequency-Domain Pitch Estimation. A Correlation-Based Pitch Estimator. Pitch Estimation Based on a "Comb Filter<170. Pitch Estimation Based on a Harmonic Sinewave Model. Glottal Pulse Onset Estimation. Multi-Band Pitch and Voicing Estimation. 11. Nonlinear Measurement and Modeling Techniques. The STFT and Wavelet Transform Revisited. Bilinear Time-Frequency Distributions. Aeroacoustic Flow in the Vocal Tract. Instantaneous Teager Energy Operator. 12. Speech Coding. Statistical Models of Speech. Scaler Quantization. Vector Quantization (VQ). Frequency-Domain Coding. Model-Based Coding. LPC Residual Coding. 13. Speech Enhancement. Introduction. Preliminaries. Wiener Filtering. Model-Based Processing. Enhancement Based on Auditory Masking. Appendix 13.A: Stochastic-Theoretic parameter Estimation. 14. Speaker Recognition. Introduction. Spectral Features for Speaker Recognition. Speaker Recognition Algorithms. Non-Spectral Features in Speaker Recognition. Signal Enhancement for the Mismatched Condition. Speaker Recognition from Coded Speech. Appendix 14.A: Expectation-Maximization (EM) Estimation. Glossary.Speech Signal Processing.Units.Databases.Index.About the Author.

Discrete-Time Speech Signal Processing: Principles and Practice

Since even before the time of Alexander Graham Bell's revolutionary invention, engineers and scientists have studied the phenomenon of speech communication with an eye on creating more efficient and effective systems of human-to-human and human-to-machine communication. Starting in the 1960s, digital signal processing (DSP), assumed a central role in speech studies, and today DSP is the key to realizing the fruits of the knowledge that has been gained through decades of research. Concomitant advances in integrated circuit technology and computer architecture have aligned to create a technological environment with virtually limitless opportunities for innovation in speech communication applications. In this text, we highlight the central role of DSP techniques in modern speech communication research and applications. We present a comprehensive overview of digital speech processing that ranges from the basic nature of the speech signal, through a variety of methods of representing speech in digital form, to applications in voice communication and automatic synthesis and recognition of speech. The breadth of this subject does not allow us to discuss any aspect of speech processing to great depth; hence our goal is to provide a useful introduction to the wide range of important concepts that comprise the field of digital speech processing. A more comprehensive treatment will appear in the forthcoming book, Theory and Application of Digital Speech Processing [101].

https://research.iaun.ac.ir/pd/mahmoodian/pdfs/UploadFile_2643.pdf

An Introduction to Digital Speech Processing

Speech is coded such that it can be generated by a pulse excitation sequence filtered by an LPC (linear preductive coding) filter. The sequence contains, in each of successive frame periods, pulses whose positions and amplitudes may be varied. These variables are selected at the coding end to reduce the error between the input and regenerated speech signals. The selection process involves derivation of an initial estimate followed by an iterative adjustment process in which pulses having a low energy contribution are tested in alternative positions and transferred to them if a reduced error results.

Multi-pulse speech coder

The general structure of this class of coders is reviewed, and the particulars of its members are discussed. The different analysis procedures are described, and the contributions of the various coder parameters to the performance of the coder are examined. Quantization procedures for each transmitted parameter are given along with examples of bit allocations. The speech quality produced by these coders is high at 16 kb/s and good at 8 kb/s, but only fair at 4.8 kb/s. The use of postprocessing techniques changes the performance at lower rates, but more research is needed to further improve the coders. >

A class of analysis-by-synthesis predictive coders for high quality speech coding at rates between 4.8 and 16 kbit/s

Although the multipulse model is conceptually simple, the problem of locating the pulses is computationally complex. The authors discuss the basic multipulse model and describe a procedure to compute the excitation with optimally adjusted amplitudes. The algorithm provides a framework for computing multipulse excitation with varying degrees of optimization and computational complexity. The authors find that speech quality depends on the pulse rate. They also find that for the same quality, female speech requires a higher pulse rate than male speech. The pitch dependence can be reduced and speech quality improved for high-pitched speakers by incorporating long delay prediction in the multipulse model. >

Amplitude optimization and pitch prediction in multipulse coders

This paper discusses the analysis techniques used to derive the excitation waveform for multipulse coding of speech. A computationally efficient formulation is derived for both covariance and correlation type analyses. These methods differ in the way block edges are treated. Several methods for pulse amplitude and position determination are given, ranging from a purely sequential one to one which reoptimizes pulse amplitudes at each step. It is shown that the reoptimization scheme has a nested structure that allows a reduction in the computations. An efficient method for pulse position coding is given. This method can essentially achieve the entropy limit for randomly placed pulses. Experimental results are given for typical configurations including computational requirements and speech quality assessments.

Efficient computation and encoding of the multipulse excitation for LPC

Block-band coders typically impose a signal delay of about 60 ms This paper reports on multipulse-LPC coding structures which reduce signal delay to 2 ms The proposed structures are based on I) a high update rate for LPC side-information, and II) the use of very short duration intervals for the placement of pulses The low delay structure imposes a relatively more uniform distribution of pulses in time The addition of pitch prediction, over very short blocks, is observed to overcome the degradation due to the uniform pulse distribution An efficient pitch prediction approach and the use of a forward-adaptive lattice filter contribute to maintaining computational requirements within the reach of modem DSP chips

M. Berouti

Papers

Efficient computation and encoding of the multipulse excitation for LPC

Reducing signal delay in multipulse coding at 16kb/s