SincNet is a neural architecture for efficiently processing raw audio samples.
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Updated
Apr 28, 2021 - Python
SincNet is a neural architecture for efficiently processing raw audio samples.
PyTorch implementation of "Generalized End-to-End Loss for Speaker Verification" by Wan, Li et al.
Speaker Identification System (upto 100% accuracy); built using Python 2.7 and python_speech_features library
Identifying people from small audio fragments
Simple d-vector based Speaker Recognition (verification and identification) using Pytorch
This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.
This repo contains my attempt to create a Speaker Recognition and Verification system using SideKit-1.3.1
Source code for paper "Who is real Bob? Adversarial Attacks on Speaker Recognition Systems" (IEEE S&P 2021)
Pytorch implementation of "Generalized End-to-End Loss for Speaker Verification"
Source Code for 'SECurity evaluation platform FOR Speaker Recognition' released in 'Defending against Audio Adversarial Examples on Speaker Recognition Systems'
Neural speaker recognition/verification system based on Kaldi and Tensorflow
Pytorch implementation of Generalized End-to-End Loss for speaker verification
this master thesis project is based on OpenAI Whisper with the goal to transcibe interviews
DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020
🔉 👦 👧 👩 👨 Speaker identification using voice MFCCs and GMM
Keras + pyTorch implimentation of "Deep Learning & 3D Convolutional Neural Networks for Speaker Verification"
Keras Implementation of Deepmind's WaveNet for Supervised Learning Tasks
Implementing VGGVox for Speaker Identification on VoxCeleb1 dataset in PyTorch.
声纹识别(Voiceprint Recognition, VPR),也称为说话人识别(Speaker Recognition),有两类,即说话人辨认(Speaker Identification)和说话人确认(Speaker Verification)
A tool for summarizing dialogues from videos or audio
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