Course details

Audio and Speech Processing by Humans and Machines

ASD Acad. year 2018/2019 Winter semester

Current academic year

3 day intensive course
Interaction between humans and machines could be greatly enhanced through communication using human sensory signals such as speech. Knowledge of human information processing is critical in the design of such human-machine interfaces. The course covers concept of signal as a carrier of information, basic principles of processing of cognitive signals, and introduces selected phenomena in auditory and visual perception. Students learn how to interpret empirical data, how to incorporate these data in models, and how to apply these models to engineering problems. Emphasis is on active research in auditory modeling that exploits special properties of speech.

Guarantor

Heřmanský Hynek, prof. Ing. (DCGM)

Language of instruction

Czech, English

Completion

Examination (oral)

Time span

  • 39 hrs lectures

Assessment points

  • 100 pts final exam

Department

Department of Computer Graphics and Multimedia (UPGM)

Lecturer

Heřmanský Hynek, prof. Ing. (DCGM)

Instructor

Heřmanský Hynek, prof. Ing. (DCGM)

Study literature

  • Ben Gold and Nelson Morgan: Speech and Audio Signal Processing, Willey and Sons 2000
  • Psutka s kolektivem: Hovorime s pocitacem cesky, Akademia Praha 2006

Syllabus of lectures

  • Day 1
    Introduction to processing of information-bearing sensory signals such as speech. Fundamentals of information theory and of pattern classification. Fundamentals of speech production. Conventional techniques for speech analysis (concept of short-term analysis, band-pass filtering, fourier-like transforms, cepstrum, linear prediction).
  • Day 2
    Fundamentals of human auditory perception. Perception of pitch and loudness. Spectral and temporal resolution of hearing. Masking in frequency and in time. Some important speech perception phenomena.
  • Day 3
    Introduction to auditory-like speech analysis techniques. Linear discriminant analysis and its use for deriving optimized spectral basis Temporal domain for speech analysis. Dynamic features of speech and RASTA technique. Multi-stream speech recognition. Recognition from temporal patterns and nonlinear discriminant mapping approaches speech.

Course inclusion in study plans

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