A Speaker Verification Workspace with Pytorch
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Updated
Apr 19, 2021 - Python
A Speaker Verification Workspace with Pytorch
Diarizing Legal Proceedings with d-vectors.
Solution Code for Signal Processing Cup - 2024 by Team EigenSharks
Training, inference, and evaluate of the speaker identification and verification model are carried out, and evasion attacks (FGSM, PGD) are performed.
说话人识别仓库-说话人表征-ResNet/VGGVox || a ready-to-use repo for Speaker Verification / Speaker Embedding with xvector
A collection of academic publications resources.
A simple probability calibration demo
Graduation project pipeline for Auto Speaker Verification system
Official implementation of the ICASSP 2024 paper: Emphasized Non-Target Speaker Knowledge in Knowledge Distillation for Speaker Verification
Pytorch implementation of Extended U-Net for Speaker Verification in Noisy Environments
Gradient Frequency Attention: Tell Neural Networks where speaker information is.
The Additive Margin MobileNet1D is a new light weight deep learning model for Speaker Recognition which is based on the MobileNetV2 architecture and the Additive Margin Softmax (AM-Softmax) loss function.)
In this repository, the wavLM model is used for quality and poor quality data for speaker verification task, and the PyCM library is used for evaluation.
Speaker verification task with ECAPA-TDNN model (trained on Persian dataset)
Speaker verification using Gaussian Mixture Model (GMM)
Repository containing code, videos and documentation of my Master Thesis work "Cascading On-Device Keyword Spotting and Speaker Verification in TinyML"
I. Thoidis, C. Gaultier, and T. Goehring, "Perceptual Analysis of Speaker Embeddings for Voice Discrimination between Machine And Human Listening," ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5
My implementation of "Generalized End-to-End Loss for Speaker Verification" (ICASSP 2018)
Graduation project web demo for Auto Speaker Verification system
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