Discrete-Time Speech Signal Processing

For advanced upper level undergraduate courses and graduate level courses in speech signal processing in Electrical Engineering covering application areas of telecommunications, speech on the internet, biometric and recognition technology, audio and speech special effects in the music and entertainment industries, and speech and hearing science. It is also useful as a reference for speech signal researchers in a university, government, or industrial laboratory.

This book provides an up-to-date, intensive introduction to the fundamental theory of discrete-time speech signal processing while presenting the state-of-the-art in speech processing research, its applications to speech modification and enhancement, speech coding, and speaker recognition, as well as areas for further advancement in the field.

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.

• 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.

• 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.

• 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.