zozyaa

zozyaa's Stars

• DmitryRyumin/AAAI-2024-Papers

  AAAI 2024 Papers: Explore a comprehensive collection of innovative research papers presented at one of the premier artificial intelligence conferences. Seamlessly integrate code implementations for better understanding. ⭐ experience the forefront of progress in artificial intelligence with this repository!

  Language:Python39316

• lukasschwab/arxiv.py

  Python wrapper for the arXiv API

  Language:Python1.1k120

• kaixindelele/ChatPaper

  Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复

  Language:Python18.3k1.9k

• ccfddl/ccf-deadlines

  ⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~

  Language:Vue6k421

• 0voice/expert_readed_books

  2021年最新总结，推荐工程师合适读本，计算机科学，软件技术，创业，**类，数学类，人物传记书籍

  7.5k2.5k

• yolain/ComfyUI-Yolain-Workflows

  Some awesome comfyui workflows in here, and they are built using the comfyui-easy-use node package.

  73372

• CosmosPsi/CosmosDocs

  13834

• corsix/amx

  Apple AMX Instruction Set

  Language:C98547

• PixArt-alpha/PixArt-alpha

  PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

  Language:Python2.7k174

• jtkim-kaist/Speech-enhancement

  Deep neural network based speech enhancement toolkit

  Language:MATLAB21062

• sunits/EnvironmentalSoundClassification

  Here, an algorithm to classify environmental sounds with the aim of providing contextual information to devices such as hearing aids for optimum performance is proposed. We use signal sub-band energy to construct signal-dependent dictionary and matching pursuit algorithms to obtain a sparse representation of a signal. The coefficients of the sparse vector are used as weights to compute weighted features. These features, along with mel frequency cepstral coefficients (MFCC), are used as feature vectors for classification. Experimental results show that the proposed method gives an accuracy as high as 95.6 %, while classifying 14 categories of environmental sound using a Gaussian mixture model (GMM). For more details, please refer to [1].

  Language:Matlab207

• simonwwt/microphoneArray

  SMIIP: microphone array

  Language:Matlab126

• respeaker/mic_hat

  2 Mic Array for Raspberry Pi

  Language:Python10332

• respeaker/usb_4_mic_array

  ReSpeaker 4 Mic Array with builtin VAD, DOA, AEC, Beamforming & NS

  Language:Python14266

• jagger2048/WebRtc_noise_suppression

  This is WebRtc noise suppression module demo.

  Language:C9429

• karolpiczak/paper-2015-esc-dataset

  ESC: Dataset for Environmental Sound Classification - paper replication data

  Language:Jupyter Notebook7620

• flashlight/wav2letter

  Facebook AI Research's Automatic Speech Recognition Toolkit

  Language:C++6.4k1k

• lijingpei2016/noiseReduction

  基于WebRTC实现iOS端音频降噪功能

  Language:C4414

• xiph/LPCNet

  Efficient neural speech synthesis

  Language:C1.1k295

• GregorR/rnnoise-nu

  Recurrent neural network for audio noise reduction, slightly improved for general use

  Language:C11920

• adityatb/noise-reduction-using-rnn

  Implements python programs to train and test a Recurrent Neural Network with Tensorflow

  Language:Python7125

• xiph/rnnoise

  Recurrent neural network for audio noise reduction

  Language:C4k888

• ShinoharaYuuyoru/NoiseReductionUsingGRU

  This is my graduation project in BIT. Title: Noise Reduction Using GRU.

  Language:Python2710