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这是我学习 PyTorch 的笔记对应的代码，点击查看 PyTorch 笔记在线电子书
Python implementation of OMLSA+IMCRA algorithm for speech enhancement.
A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.
Code for DCASE 2020 task 1a and task 1b.
Code repository for the paper Direction of Arrival Estimation of Sound Sources Using Icosahedral CNNs
Code repository for the paper Robust Sound Source Tracking Using SRP-PHAT and 3D Convolutional Neural Networks
A python implementation of “SRP-DNN: Learning Direct-Path Phase Difference for Multiple Moving Sound Source Localization” [ICASSP 2022]
The Official PyTorch Implementation of FN-SSL & IPDnet for Sound Source Localization
Neural Network based Sound Source Localization Models
Baseline method for sound event localization task of DCASE 2022 challenge
Sound event localization, detection, and tracking of multiple overlapping and moving sources in 2D spherical space using convolutional recurrent neural network
Classical algorithms of sound source localization with beamforming, TDOA and high-resolution spectral estimation.
Easy to use Beamformers for multi-channel speech separation/enhancement
A timeline of the latest AI models for audio generation, starting in 2023!
A LSTM for voice activity detection. In fact, this is a homework which I didn't expected.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.
The official repo: "McNet: Fuse Multiple Cues for Multichannel Speech Enhancement", ICASSP 2023
Muzic: Music Understanding and Generation with Artificial Intelligence
microphone array speech generator (MASG) in room acoustic
Core Engine of Singing Voice Conversion & Singing Voice Clone
Source code for "FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control"
Official Implementation of "Multitrack Music Transformer" (ICASSP 2023)
The simplest, fastest repository for training/finetuning medium-sized GPTs.