Lehrinhalte
Algorithms of speech and audio signal processing: Introduction to the models of speech and audio signals and basic methods of audio signal processing. Procedures of codebook based processing and audio coding. Beamforming for spatial filtering and noise reduction for spectral filtering. Cepstral filtering and fundamental frequency estimation. Mel-filterind cepstral coefficients (MFCCs) as basis for speaker detection and speech recognition. Classification methods based on GMM (Gaussian mixture models) and speech recognition with HMM (Hidden markov models). Introduction to the methods of music signal processing, e.g. Shazam-App or beat detection.
Literatur
Slides (for further details see homepage of the lecture)
Voraussetzungen
Knowlegde about satistical signal processing is required (lecture Digital Signal Processing). Desired
but not mandatory is knowledge about adaptive filters.
Online-Angebote
Moodle
Algorithms of speech and audio signal processing: Introduction to the models of speech and audio signals and basic methods of audio signal processing. Procedures of codebook based processing and audio coding. Beamforming for spatial filtering and noise reduction for spectral filtering. Cepstral filtering and fundamental frequency estimation. Mel-filterind cepstral coefficients (MFCCs) as basis for speaker detection and speech recognition. Classification methods based on GMM (Gaussian mixture models) and speech recognition with HMM (Hidden markov models). Introduction to the methods of music signal processing, e.g. Shazam-App or beat detection.
Literatur
Slides (for further details see homepage of the lecture)
Voraussetzungen
Knowlegde about satistical signal processing is required (lecture Digital Signal Processing). Desired
but not mandatory is knowledge about adaptive filters.
Online-Angebote
Moodle
- Lehrende: Henning Puder
Semester: WT 2020/21