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This is the implementation of paper <Additive Margin Softmax for Face Verification>
Implementation of the paper "One-class Learning towards Generalized Voice Spoofing Detection"
JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with Squeeze-Excitation and Residual neTworks (ASSERT).
This repo is for the SPL paper "Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap"
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
A curated list of awesome Speaker Diarization papers, libraries, datasets, and other resources.
Pytorch implementation of the paper "Circle Loss: A Unified Perspective of Pair Similarity Optimization"
Code for Yun Wang's PhD Thesis: Polyphonic Sound Event Detection with Weak Labeling
Repo for our pooling approach on the DCASE2018 task4
Deep neural networks for voice conversion (voice style transfer) in Tensorflow
PyTorch implementation of the Factorized TDNN (TDNN-F) from "Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks" and Kaldi
Gradient Reversal Layer for Domain Adaptation
This is now the official location of the Kaldi project.
In this work I investigate the speech command task developing and analyzing deep learning models. The state of the art technology uses convolutional neural networks (CNN) because of their intrinsic nature of learning correlated represen- tations as is the speech. In particular I develop different CNNs trained on the Google Speech Command Dataset and tested on different scenarios. A main problem on speech recognition consists in the differences on pronunciations of words among different people: one way of building an invariant model to variability is to augment the dataset perturbing the input. In this work I study two kind of augmentations: the Vocal Tract Length Perturbation (VTLP) and the Synchronous Overlap and Add (SOLA) that locally perturb the input in frequency and time respectively. The models trained on augmented data outperforms in accuracy, precision and recall all the models trained on the normal dataset. Also the design of CNNs has impact on learning invariances: the inception CNN architecture in fact helps on learning features that are invariant to speech variability using different kind of kernel sizes for convolution. Intuitively this is because of the implicit capability of the model on detecting different speech pattern lengths in the audio feature.
Local Pairwise Linear Discriminant Analysis
Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning
A tensorflow implementation of my paper Combining beamforming and deep neural networks for multi-channel speech extraction
netVLAD implementation in TensorFlow
TensorFlow implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".
Simple package that makes your generator work in background thread
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
Deep speaker embeddings in PyTorch, including x-vectors. Code used in this work: https://arxiv.org/abs/2007.16196
Pytorch implementation of Quadratic Additive Angular Margin Loss for Face Recognition
Robust Fisher Linear Discriminant Analysis
A library for soundscape synthesis and augmentation
Speech Enhancement Generative Adversarial Network in TensorFlow
Simple Tensorflow Implementation of "A Structured Self-attentive Sentence Embedding" (ICLR 2017)
Tensorflow implementation of generalized end-to-end loss for speaker verification
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.