Speech and Audio Processing

A. Basics

1. Human Speech production & Hearing
   • Speech Production: Anatomy & Models
   • Hearing: Anatomy & psychoacoustics
2. Signal Representation
   • Long-term description vs Short-term description
   • Stochastic Properties
   • Spectral representation & Cepstral representation

B. Source Coding for speech & audio signals

1. Data compression
2. Quantization
3. Linear Prediction
4. Coding in Time Domain
5. Coding in Frequency Domain
   • MP3, AAC

C. Basics of Automatic Speech Recognition (ASR)

1. Basics
2. Approaches to ASR
   • Acoustic-phonetic approach
   • Pattern Recognition approach
   • AI approach
3. Acoustic Modeling
   • Feature Extraction
   • Feature Transformation
   • Pattern Comparison
4. Hidden Markov Models
   • Properties of HMM
   • Evaluation of model: Forward Algorithm
   • Search for hidden str of obs: Viterbi Algorithm
   • Optimization of model by training: Baum-Welch Algorithm

D. Basics of Text-to-Speech (TTS) Translation

1. System Architecture
2. Text Analyis
3. Phonetic Analysis
4. Prosody
5. Speech Synthesis
   • Basics
   • Formant Synthesis
   • Concatenative Synthesis
   • Prosodic Modification of Speech: OLA, SOLA, PSOLA

E. Signal Enhancement

1. Signal Procesisng Methods
   • Single-channel acquisition & reproduction
   • Multi-channel acquisition & reproduction: Beamforming
2. Acoustic echo cancellation (AEC)
3. Noise Reduction
4. Dereverbation
5. MIMO Systems for Blind Signal Acquisition: TRINICON