L-SpEx: Localized Target Speaker Extraction

Related tags

Audio L-SpEx
Overview

L-SpEx: Localized Target Speaker Extraction

The data configuration and simulation of L-SpEx. The code scripts will be released in the future.

Data Generation:

  1. Download LibriSpeech(dev-clean.tar.gz, test-clean.tar.gz, train-clean-100.tar.gz, train-clean-360.tar.gz) and Wham_noise(wham_noise.zip). And move the librispeech and wham_noise to 'data_simulation/MC-Libri2Mix/spatilize_mixture/'

  2. generate the RIRs information.

python run_sample_reverb_libri.py
  1. generate the MC-Libri2Mix dataset using RIRs information.
./generate_librimix.sh YOUR_SAVE_PATH

Environments:

python: 3.8.3

Pytorch: 1.6

You might also like...
 Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson

Conference planning tool: CfP, scheduling, speaker management
Conference planning tool: CfP, scheduling, speaker management

pretalx is a conference planning tool focused on providing the best experience for organisers, speakers, reviewers, and attendees alike. It handles th

Conference planning tool: CfP, scheduling, speaker management
Conference planning tool: CfP, scheduling, speaker management

pretalx is a conference planning tool focused on providing the best experience for organisers, speakers, reviewers, and attendees alike. It handles th

SC-GlowTTS: an Efficient Zero-Shot Multi-Speaker Text-To-Speech Model

SC-GlowTTS: an Efficient Zero-Shot Multi-Speaker Text-To-Speech Model Edresson Casanova, Christopher Shulby, Eren Gölge, Nicolas Michael Müller, Frede

This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.

UIS-RNN Overview This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm. UIS-RNN solves the problem of s

ERISHA is a mulitilingual multispeaker expressive speech synthesis framework. It can transfer the expressivity to the speaker's voice for which no expressive speech corpus is available.
ERISHA is a mulitilingual multispeaker expressive speech synthesis framework. It can transfer the expressivity to the speaker's voice for which no expressive speech corpus is available.

ERISHA: Multilingual Multispeaker Expressive Text-to-Speech Library ERISHA is a multilingual multispeaker expressive speech synthesis framework. It ca

PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation

StyleSpeech - PyTorch Implementation PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. Status (2021.06.09

PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation

StyleSpeech - PyTorch Implementation PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. Status (2021.06.13

Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS)
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS)

This repository is an implementation of Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. Feel free to check my thesis if you're curious or if you're looking for info I haven't documented. Mostly I would recommend giving a quick look to the figures beyond the introduction.

Use android as mic/speaker for ubuntu

Pulse Audio Control Panel Platforms Requirements sudo apt install ffmpeg pactl (already installed) Download Download the AppImage from release page ch

TalkNet: Audio-visual active speaker detection Model
TalkNet: Audio-visual active speaker detection Model

Is someone talking? TalkNet: Audio-visual active speaker detection Model This repository contains the code for our ACM MM 2021 paper, TalkNet, an acti

neural network based speaker embedder

Content What is deepaudio-speaker? Installation Get Started Model Architecture How to contribute to deepaudio-speaker? Acknowledge What is deepaudio-s

Look Who’s Talking: Active Speaker Detection in the Wild

Look Who's Talking: Active Speaker Detection in the Wild Dependencies pip install -r requirements.txt In addition to the Python dependencies, ffmpeg

Official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch.

Multi-speaker DGP This repository provides official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch. O

Demo for the paper
Demo for the paper "Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation"

Streaming speaker diarization Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation by Juan Manuel Coria, Hervé

Demo for the paper
Demo for the paper "Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation"

Streaming speaker diarization Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation by Juan Manuel Coria, Hervé

Original implementation of the pooling method introduced in "Speaker embeddings by modeling channel-wise correlations"

Speaker-Embeddings-Correlation-Pooling This is the original implementation of the pooling method introduced in "Speaker embeddings by modeling channel

SpeechNAS Better Trade off between Latency and Accuracy for Large Scale Speaker Verification
SpeechNAS Better Trade off between Latency and Accuracy for Large Scale Speaker Verification

SpeechNAS Better Trade off between Latency and Accuracy for Large Scale Speaker Verification

Unofficial reimplementation of ECAPA-TDNN for speaker recognition (EER=0.86 for Vox1_O when train only in Vox2)

Introduction This repository contains my unofficial reimplementation of the standard ECAPA-TDNN, which is the speaker recognition in VoxCeleb2 dataset

Owner
Meng Ge
Meng Ge
Use android as mic/speaker for ubuntu

Pulse Audio Control Panel Platforms Requirements sudo apt install ffmpeg pactl (already installed) Download Download the AppImage from release page ch

null 19 Dec 1, 2022
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

A Python library for audio feature extraction, classification, segmentation and applications This doc contains general info. Click here for the comple

Theodoros Giannakopoulos 5.1k Jan 2, 2023
Audio features extraction

Yaafe Yet Another Audio Feature Extractor Build status Branch master : Branch dev : Anaconda : Install Conda Yaafe can be easily install with conda. T

Yaafe 231 Dec 26, 2022
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

A Python library for audio feature extraction, classification, segmentation and applications This doc contains general info. Click here for the comple

Theodoros Giannakopoulos 3.8k Feb 17, 2021
LibXtract is a simple, portable, lightweight library of audio feature extraction functions.

LibXtract LibXtract is a simple, portable, lightweight library of audio feature extraction functions. The purpose of the library is to provide a relat

Jamie Bullock 215 Nov 16, 2022
spafe: Simplified Python Audio-Features Extraction

spafe aims to simplify features extractions from mono audio files. The library can extract of the following features: BFCC, LFCC, LPC, LPCC, MFCC, IMFCC, MSRCC, NGCC, PNCC, PSRCC, PLP, RPLP, Frequency-stats etc. It also provides various filterbank modules (Mel, Bark and Gammatone filterbanks) and other spectral statistics.

Ayoub Malek 310 Jan 1, 2023
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au

pyannote 2.1k Dec 31, 2022
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au

pyannote 2.2k Jan 9, 2023
Source code for paper "Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling", AAAI 2021

ATLOP Code for AAAI 2021 paper Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling. If you make use of this co

Wenxuan Zhou 146 Nov 29, 2022
Official PyTorch implementation of MX-Font (Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts)

Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1

Clova AI Research 97 Dec 23, 2022