orangejuice1007
Follow
Stars
The Microsoft Scalable Noisy Speech Dataset (MS-SNSD) is a noisy speech dataset that can scale to arbitrary sizes depending on the number of speakers, noise types, and Speech to Noise Ratio (SNR) l…
Matlab implementation of the paper Noise Spectrum Estimation in Adverse Environments: Improved Minima Controlled Recursive Averaging
ChatGLM3 series: Open Bilingual Chat LLMs | 开源双语对话语言模型
Fine-tuning ChatGLM-6B with PEFT | 基于 PEFT 的高效 ChatGLM 微调
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multi…
This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.
The PyTorch-based audio source separation toolkit for researchers
Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.
deep clustering method for single-channel speech separation
Universal Deep neural network based speech enhancement demo and tools, well pre-trained DNN model
Pytorch implements Deep Clustering: Discriminative Embeddings For Segmentation And Separation
This is a mandarin version of speech separation dataset like WSJMix and LibriMix
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement
Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network
A must-read paper for speech separation based on neural networks
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a ca…
Deezer source separation library including pretrained models.
A PyTorch implementation of DNN-based source separation.
Data preparation for separation
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch
基于Pytorch的文本分类框架，支持TextCNN、Bert、Electra等。
NLP 领域常见任务的实现，包括新词发现、以及基于pytorch的词向量、中文文本分类、实体识别、摘要文本生成、句子相似度判断、三元组抽取、预训练模型等。