dla

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一套面向音频处理的深度学习实战代码集,覆盖语音识别、说话人验证、关键词唤醒、语音合成与音色转换等任务,可直接参考实现来训练和微调模型。

Deep learning for audio processing

暂无版本778star +1 / 7 天125fork同步于 2026-11-10 17:56 UTC

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项目说明

由 README 自动翻译提炼

HSE 音频深度学习课程材料,按周提供讲义与研讨会代码,覆盖语音识别与音源分离

一套面向音频处理的深度学习实战代码集,覆盖语音识别、说话人验证、关键词唤醒、语音合成与音色转换等任务,可直接参考实现来训练和微调模型。

核心能力

  • 按 week01 至 week06 分目录组织讲义与研讨会材料
  • 覆盖 DSP、频谱图与 MFCC 等信号处理基础
  • 讲解 CTC、DeepSpeech2、Conformer 与 Whisper 等 ASR 模型
  • 介绍 wav2vec 2.0、HuBERT 等语音自监督学习方法
  • 涉及 Demucs、DCCRN 等音源分离与降噪架构

容易踩的坑

这是课程材料仓库,不是可直接安装的软件包,需按各 week 目录下 README 的说明操作;讲义录像主要为俄语,仅部分周有英文录像;作业与项目部分标注为 TBA,尚未提供

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    README 原文

    未翻译

    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 2026 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
    • week03 Automatic Speech Recognition I

      • Lecture: Metrics, Datasets, Connectionist Temporal Classification (CTC), DeepSpeech2, Conformer, Beam Search, Language models
      • Seminar: Audio Augmentations, WER and CER, CTC Decoding
    • week04 Automatic Speech Recognition II

      • Lecture: LAS, Hybrid CTC/Attention, OpenAI Whisper, RNN-T, Streaming ASR, Decoder-only ASR
      • Seminar: Whisper: greedy decoding, prompting, alignment in cross-attention, language forcing
    • week05 Automatic Speech Recognition III and Audio SSL

      • Lecture: Self-Supervised Learning for Speech, wav2vec 2.0, HuBERT, BEST-RQ, GigaAM, LLM-based ASR, Delayed Streams Modeling, Encoder-free Architectures
    • week06 Source Separation I

      • Lecture: A review of general Source Separation and Denoising, Encoder-Decoder-Separator architectures, Demucs family, DCCRN, FullSubNet+, BandSplitRNN
      • Seminar: Metrics

    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