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 2022 at the CS Faculty of HSE
Syllabus
-
week01 Introduction to Course
- Lecture: Introduction to Course
- Seminar: Intro in
pytorch
-
week02 Introduction to Digital Signal Processing
- Lecture: Signals, Fourier Transform, spectrograms, MelScale, MFCC
- Seminar: DSP in practice, spectrogram creation, training a model for audio MNIST
-
week03 Speech Recognition I
- Lecture: Metrics, datasets, Connectionist Temporal Classification (CTC), Listen Attend and Spell (LAS), Beam Search
- Seminar: TODO
-
week04 Speech Recognition II
- Lecture: RNN-T, language model fusion, Byte-Pair Encoding (BPE)
- Seminar: Forced alignment
Homeworks
- hw1_asr Training speech recognition model
Resources
- Lecture recordings on YouTube (in russian): YouTube
Contributors & course staff
Course materials and teaching performed by