markovka17/dla

Deep learning for audio processing

Jupyter Notebook

769

191 commits

updated Sep 25, 2026

See the code

README

logo5v1

Deep Learning for Audio (DLA)

  • Lecture and seminar materials for each week are in ./week* folders, see README.md for materials and instructions
  • Any technical issues, ideas, bugs in course materials, contribution ideas - add an issue
  • The current version of the course is conducted in autumn 2025 at the CS Faculty of HSE.

For previous years versions, see Past Versions section.

Syllabus

  • week01 Introduction to Course

    • Lecture: Introduction to Course + Inspiration
    • Seminar: Free talk
    • Self-Study: Introduction to PyTorch and basic devOps
  • week02 Introduction to Digital Signal Processing

    • Lecture: Signals, Fourier Transform, spectrograms, MelScale, MFCC
    • Seminar: DSP in practice, spectrogram creation, IRF, frequency filtering

TBA

Homeworks and Projects

TBA

See our project template.

Resources

Some of the weeks have English recordings. See the corresponding sub-directories.

Contributors & course staff

Course materials and teaching (in different years) were delivered by:

Past Versions

deep-learning
keyword-spotting
signal-processing
speaker-verification
speech-recognition
tts
voice-conversion

markovka17/dla

Deep learning for audio processing

Jupyter Notebook

769

191 commits

updated Sep 25, 2026

See the code

README

logo5v1

Deep Learning for Audio (DLA)

  • Lecture and seminar materials for each week are in ./week* folders, see README.md for materials and instructions
  • Any technical issues, ideas, bugs in course materials, contribution ideas - add an issue
  • The current version of the course is conducted in autumn 2025 at the CS Faculty of HSE.

For previous years versions, see Past Versions section.

Syllabus

  • week01 Introduction to Course

    • Lecture: Introduction to Course + Inspiration
    • Seminar: Free talk
    • Self-Study: Introduction to PyTorch and basic devOps
  • week02 Introduction to Digital Signal Processing

    • Lecture: Signals, Fourier Transform, spectrograms, MelScale, MFCC
    • Seminar: DSP in practice, spectrogram creation, IRF, frequency filtering

TBA

Homeworks and Projects

TBA

See our project template.

Resources

Some of the weeks have English recordings. See the corresponding sub-directories.

Contributors & course staff

Course materials and teaching (in different years) were delivered by:

Past Versions

deep-learning
keyword-spotting
signal-processing
speaker-verification
speech-recognition
tts
voice-conversion

Languages

Jupyter Notebook

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