Pytorch 的声音分类实现支持 EcapaTdnn、PANNS、TDNN、Res2Net、ResNetSE 等模型,以及多种预处理方法。
audioclassification 开源项目推荐(18 个)
audioclassification 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 全部 18
GitHub 共 18 个仓库,已全部展示基于Tensorflow实现声音分类,博客地址:
This repository is built with a focus on practical ways to obtain and work with the audio data of audioset. You can use this repository to download and precprocess audioset wav files for running the recipies of Audio Spectogram Transformer (AST) and Masked Autoencoder that listen (Audio - MAE).
This project leverages Convolutional Neural Networks (CNNs) to perform real-time audio classification in rainforest environments, detecting sounds such as chainsaws, truck engines, and storms. Audio data, sourced from UrbanSound8K and rainforest recordings, is preprocessed into spectrograms using Librosa, while synthetic soundscapes are generated w
This repository contains code/papers/research on Speech or Audio Classification
BirdCLEF 2025 soundscape classification project using deep learning (SeresNeXt26t) with PyTorch, pseudo-labeling, and audio preprocessing for bird species identification.
该项目在 GitHub 上没有填写描述
A Convolutional Neural Network which is trained to detect COVID 19 even in asymptotic patients using only cough recordings.
This project builds a deep-learning-based heartbeat sound classification system using MFCC features and multiple models including CNN, BiLSTM, and a Hybrid CNN–BiLSTM architecture. The system detects and classifies heart sounds into normal, murmur, and artifact categories, supporting early cardiac abnormality detection.
Speech Emotion Recognition, abbreviated as SER, is the act of attempting to recognize human emotion and affective states from speech. This is capitalizing on the fact that voice often reflects underlying emotion through tone and pitch. This is also the phenomenon that animals like dogs and horses employ to be able to understand human emotion.
Tiny offline voice-command system for Raspberry Pi 4: Astra wake-word detection and command recognition with INT8 ONNX Runtime.
Ancri Carlo, UniMi
Dataset for CABA: Clasificador Automatico de Botellas por Acustica (Automatic Acustic Bottle Classifier)
Ancri Carlo, UniMi.
Classical ML pipeline for BirdCLEF+ 2026: identifying 206 wildlife species from Pantanal audio recordings with hand-engineered features, no neural networks. 0.922 macro ROC-AUC.
This is a space where I share my personal portfolio :)
A novel, model-agnostic Explainable AI (XAI) framework for audio classification. Introduces RISE-SPEC, RISE-WAVE, and RISE-AUDIO, demonstrating superior interpretability over baseline methods like RISE, LIME, and Grad-CAM.
A deep learning model that can detect the presence of capuchin bird calls in audio clips
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 18 个项目;原始页面见 https://github.com/topics/audioclassification。
- 该话题在 GitHub 上共有 18 个仓库, 本站收录的是其中最热门的 18 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 18 个项目累计 736 Star,覆盖 3 种主要语言,数据更新于 2026-11-12。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。