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.
This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.
Simple d-vector based Speaker Recognition (verification and identification) using Pytorch
Speaker Identification System (upto 100% accuracy); built using Python 2.7 and python_speech_features library
Identifying people from small audio fragments
This repo contains my attempt to create a Speaker Recognition and Verification system using SideKit-1.3.1
Pytorch implementation of "Generalized End-to-End Loss for Speaker Verification"
Source code for paper "Who is real Bob? Adversarial Attacks on Speaker Recognition Systems" (IEEE S&P 2021)
The official implementation of SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model
Pytorch implementation of Generalized End-to-End Loss for speaker verification
A tool for summarizing dialogues from videos or audio
Official Implementation of the work "Audio Mamba: Bidirectional State Space Model for Audio Representation Learning"
Keras Implementation of Deepmind's WaveNet for Supervised Learning Tasks
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)
🔉 👦 👧 👩 👨 Speaker identification using voice MFCCs and GMM
Speakerbox: Fine-tune Audio Transformers for speaker identification.
this master thesis project is based on OpenAI Whisper with the goal to transcibe interviews
Implementation of the paper "Attentive Statistics Pooling for Deep Speaker Embedding" in Pytorch
Neural speaker recognition/verification system based on Kaldi and Tensorflow
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