aishinchi's repositories

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Cone-of-Silence

The Cone of Silence:

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asteroid

The PyTorch-based audio source separation toolkit for researchers || Current highlight : we got our WHAMR results check it out here !

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CNTK

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

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Comparison-of-Blind-Source-Separation-techniques

Compare AIRES BSS with TRINICON, ILRMA and AuxIVA (online and offline versions)

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Components-Loss

Components loss for neural networks in mask-based speech enhancement

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Conv-TasNet

A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).

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DeepXi

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2. For speech enhancement and robust ASR.

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DNS-Challenge

This repo contains the scripts, models, and required files for the ICASSP 2021 Deep Noise Suppression (DNS) Challenge.

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Dual-Path-RNN-Pytorch

Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch

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dual-path-RNNs-DPRNNs-based-speech-separation

A PyTorch implementation of dual-path RNNs (DPRNNs) based speech separation described in "Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation".

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ganhacks

starter from "How to Train a GAN?" at NIPS2016

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HelloWorld3

试试c++同步

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kaldi

This is now the official location of the Kaldi project.

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Keras-GAN

Keras implementations of Generative Adversarial Networks.

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Leetcode

my leetcode

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libri_css

Libri-CSS: dataset and evaluation pipeline

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MetricGAN

MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement (ICML 2019, with Travel awards)

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MetricGAN_v1

Our implement of MetricGAN.

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speechbrain

A PyTorch-based Speech Toolkit

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SpEx_Plus

SpEx+(tied) source code

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TAC

transform-average-concatenate (TAC) method for end-to-end microphone permutation and number invariant ad-hoc beamforming.

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tensorflow

Computation using data flow graphs for scalable machine learning

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Wave-U-Net-for-Speech-Enhancement

Implement [Wave-U-Net](https://arxiv.org/abs/1806.03185) by PyTorch, and migrate it to the speech enhancement area.

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