Athenaan open-source implementation of sequence-to-sequence based speech processing engine
Stars: ✭ 542 (+11.75%)
VAENAR-TTSPyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
Stars: ✭ 66 (-86.39%)
SpeechsplitUnsupervised Speech Decomposition Via Triple Information Bottleneck
Stars: ✭ 266 (-45.15%)
Hifi GanHiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
Stars: ✭ 325 (-32.99%)
esp32-fliteSpeech synthesis running on ESP32 based on Flite engine.
Stars: ✭ 28 (-94.23%)
He4o和(he for objective-c) —— “信息熵减机系统”
Stars: ✭ 284 (-41.44%)
EspeakeSpeak NG is an open source speech synthesizer that supports 101 languages and accents.
Stars: ✭ 339 (-30.1%)
Recycle GanUnsupervised Video Retargeting (e.g. face to face, flower to flower, clouds and winds, sunrise and sunset)
Stars: ✭ 367 (-24.33%)
EmotionalConversionStarGANThis repository contains code to replicate results from the ICASSP 2020 paper "StarGAN for Emotional Speech Conversion: Validated by Data Augmentation of End-to-End Emotion Recognition".
Stars: ✭ 92 (-81.03%)
Cognitive Speech TtsMicrosoft Text-to-Speech API sample code in several languages, part of Cognitive Services.
Stars: ✭ 312 (-35.67%)
MVGLTCyb 2018: Graph learning for multiview clustering
Stars: ✭ 26 (-94.64%)
Glow TtsA Generative Flow for Text-to-Speech via Monotonic Alignment Search
Stars: ✭ 284 (-41.44%)
Pytorch CortexnetPyTorch implementation of the CortexNet predictive model
Stars: ✭ 349 (-28.04%)
ParakeetPAddle PARAllel text-to-speech toolKIT (supporting WaveFlow, WaveNet, Transformer TTS and Tacotron2)
Stars: ✭ 279 (-42.47%)
Disentangling VaeExperiments for understanding disentanglement in VAE latent representations
Stars: ✭ 398 (-17.94%)
CorexCorEx or "Correlation Explanation" discovers a hierarchy of informative latent factors. This reference implementation has been superseded by other versions below.
Stars: ✭ 266 (-45.15%)
MlxtendA library of extension and helper modules for Python's data analysis and machine learning libraries.
Stars: ✭ 3,729 (+668.87%)
UEGAN[TIP2020] Pytorch implementation of "Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network"
Stars: ✭ 68 (-85.98%)
Enlightengan[IEEE TIP'2021] "EnlightenGAN: Deep Light Enhancement without Paired Supervision" by Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang
Stars: ✭ 434 (-10.52%)
learning-topology-synthetic-dataTensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
Stars: ✭ 22 (-95.46%)
DgiDeep Graph Infomax (https://arxiv.org/abs/1809.10341)
Stars: ✭ 326 (-32.78%)
ML2017FALLMachine Learning (EE 5184) in NTU
Stars: ✭ 66 (-86.39%)
Voice BuilderAn opensource text-to-speech (TTS) voice building tool
Stars: ✭ 362 (-25.36%)
srVAEVAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.
Stars: ✭ 56 (-88.45%)
Chinese Ufldl Tutorial[UNMAINTAINED] 非监督特征学习与深度学习中文教程,该版本翻译自新版 UFLDL Tutorial 。建议新人们去学习斯坦福的CS231n课程,该门课程在网易云课堂上也有一个配有中文字幕的版本。
Stars: ✭ 303 (-37.53%)
PICParametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020
Stars: ✭ 41 (-91.55%)
SimclrPyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.
Stars: ✭ 293 (-39.59%)
PaseProblem Agnostic Speech Encoder
Stars: ✭ 348 (-28.25%)
Awesome VaesA curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
Stars: ✭ 418 (-13.81%)
Pytorch Vsumm ReinforceAAAI 2018 - Unsupervised video summarization with deep reinforcement learning (PyTorch)
Stars: ✭ 283 (-41.65%)
Mmt[ICLR-2020] Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification.
Stars: ✭ 345 (-28.87%)
SealionThe first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
Stars: ✭ 278 (-42.68%)
Corex topicHierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
Stars: ✭ 439 (-9.48%)
Paragraph Vectors📄 A PyTorch implementation of Paragraph Vectors (doc2vec).
Stars: ✭ 337 (-30.52%)
L2cLearning to Cluster. A deep clustering strategy.
Stars: ✭ 262 (-45.98%)
Comprehensive-Tacotron2PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques to enforce the robustness and efficiency of the model.
Stars: ✭ 22 (-95.46%)
Multilingual text to speechAn implementation of Tacotron 2 that supports multilingual experiments with parameter-sharing, code-switching, and voice cloning.
Stars: ✭ 324 (-33.2%)
voice-conversionan tutorial implement of voice conversion using pytorch
Stars: ✭ 26 (-94.64%)
GanttsPyTorch implementation of GAN-based text-to-speech synthesis and voice conversion (VC)
Stars: ✭ 460 (-5.15%)
adareg-monodispnetRepository for Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction (CVPR2019)
Stars: ✭ 22 (-95.46%)
Beta VaePytorch implementation of β-VAE
Stars: ✭ 326 (-32.78%)
dti-clustering(NeurIPS 2020 oral) Code for "Deep Transformation-Invariant Clustering" paper
Stars: ✭ 60 (-87.63%)
EspnetEnd-to-End Speech Processing Toolkit
Stars: ✭ 4,533 (+834.64%)
altairAssessing Source Code Semantic Similarity with Unsupervised Learning
Stars: ✭ 42 (-91.34%)
SelflowSelFlow: Self-Supervised Learning of Optical Flow
Stars: ✭ 319 (-34.23%)
back2futureUnsupervised Learning of Multi-Frame Optical Flow with Occlusions
Stars: ✭ 39 (-91.96%)
SprocketVoice Conversion Tool Kit
Stars: ✭ 425 (-12.37%)
kwxBERT, LDA, and TFIDF based keyword extraction in Python
Stars: ✭ 33 (-93.2%)
NnmnkwiiLibrary to build speech synthesis systems designed for easy and fast prototyping.
Stars: ✭ 308 (-36.49%)
PiCIEPiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)
Stars: ✭ 102 (-78.97%)
Libfaceidlibfaceid is a research framework for prototyping of face recognition solutions. It seamlessly integrates multiple detection, recognition and liveness models w/ speech synthesis and speech recognition.
Stars: ✭ 354 (-27.01%)
PysptkA python wrapper for Speech Signal Processing Toolkit (SPTK).
Stars: ✭ 297 (-38.76%)
Sc Sfmlearner ReleaseUnsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video (NeurIPS 2019)
Stars: ✭ 468 (-3.51%)
PyodA Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Stars: ✭ 5,083 (+948.04%)
Lifting From The Deep ReleaseImplementation of "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image"
Stars: ✭ 425 (-12.37%)