In this lecture the basics of speech, audio, and music signal processing are treated.
You will learn a lot about fundamentals as well as about recent research in this interesting field of signal processing.
The topics of the lecture are:
- 1. Introduction to the properties of speech and audio signals
- 2. Basic methods of audio signal processing
- a. Frequency analysis methods
- b. Estimation of the auto correlation functions (ACF) and power spectral density functions (PSD)
- c. Tracking and detection methods including computational efficient calculation methods
- d. Measurements of room impulse responses and reverberation times
- e. Typically used filter methods with corresponding design methods
- 3. Methods for codebook processing
- a. Principle
- b. Training of codebooks
- c. Efficient codebook search
- 4. Audio coding: prediction coding, line spectral frequencies (LSF), code excited linear prediction (CELP)
- 5. Noise reduction and beamforming
- 6. Cepstral processing as one important tool of speech processing, Example: Cepstral smoothing for noise reduction to avoid the “Musical Tones” problem
- 7. Methods for pitch frequency calculation and applications
- 8. “Mel frequency cepstral coefficients” (MFCC) as one important feature analysis in speech processing
- 9. Speaker detection based on MFCCs combined with LDA (linear discriminant anaylsis) and PCA (principle component analysis)
- 10. Hidden Markov Models (HMM)
- 11. Speech regognition
- 12. Acoustic classification methods: Bayes methods, Gaussians mixture models (GMM), etc.
- 13. Music signal processing, e.g. beat detection