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Name: Helin Wang
Type: User
Company: THU & PKU & JHU
Bio: PhD student at Johns Hopkins University, interested in AI for Audio & Speech Processing.
Location: Baltimore, US
Name: Helin Wang
Type: User
Company: THU & PKU & JHU
Bio: PhD student at Johns Hopkins University, interested in AI for Audio & Speech Processing.
Location: Baltimore, US
Implements https://arxiv.org/abs/1711.05101 AdamW optimizer, cosine learning rate scheduler and "Cyclical Learning Rates for Training Neural Networks" https://arxiv.org/abs/1506.01186 for PyTorch framework
triplet loss on Acoustic Scene Classification-PyTorch
Pytorch implementation of the paper : Modeling Label Dependencies for Audio Tagging with Graph Convolutional Network
Capturing attentive temporal relations in semantic neighborhood for ASC
Pytorch code for the paper 'Attention-based Atrous Convolutional Neural Networks: Visualisation and Understanding Perspectives of Acoustic Scenes', by Zhao Ren, Qiuqiang Kong, Jing Han, Mark Plumbley, Björn Schuller.
Aty-TTS: Improving fairness for spoken language understanding in atypical speech with Text-to-Speech
Download and create a tfreader for the audioset dataset
Automatic speech annotator processing speech with voice activaty detection, overlapping speech detection, speaker diarization and automatic speech recognition
PyTorch implementations of neural network models for Babycry sound detection, including training process and test demo. Based on DCASE2017 Task2: Detection of rare sound events.
code of Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations (CVPR2020 oral)
Multilingual CLIP - Semantic Image Search in 100 languages
Code for Yun Wang's PhD Thesis: Polyphonic Sound Event Detection with Weak Labeling
A CNN model (RseNet) for image classification( CIFAR-10), including filter and output of layers visualization.
Official PyTorch implementation of "Improved Techniques for Training Single-Image GANs"
A pytorch implementation of the paper : Acoustic Scene Classification with Multiple Decision Schemes.
Dcase2019 Task1a using audio feature module.
DCASE2019 Challenge Task 1 baseline system
A Pytorch implementation of the DCASE2020 Task6 by PKU team : Automated Audio Captioning With Temporal Attention
This is the code of PKU team for DCASE 2021 Task 6.
Source code and demo for INTERPSEECH 2023 paper: DuTa-VC: A Duration-aware Typical-to-atypical Voice Conversion Approach with Diffusion Probabilistic Model
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Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.