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audasc

Adversarial Unsupervised Domain Adaptation for Acoustic Scene Classification

audio-classification-using-bag-of-frames-approach

Classification of different categories of audio clips, especially non speech sounds using Bag-of-Frames approach.

audio_classification_using_lstm

Classification of Urban Sound Audio Dataset using LSTM-based model.

audiophi

VGGish

bagofframes4acousticsceneclassification

Bag of Frames(KMeans/GMM) for Acoustic Scene Classfication

bilstm

cmu-thesis

Code for Yun Wang's PhD Thesis: Polyphonic Sound Event Detection with Weak Labeling

cnn-lstm-bilstm-deepcnn-clstm-in-pytorch

In pytorch Learing Neural Networks likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

cv_objectdetection

CV project

dcase2017_task4_cvssp

code for our 1st prize system to win the DCASE2017 task4 challenge

dcase_util

A collection of utilities for Detection and Classification of Acoustic Scenes and Events

distinct-events-asc

Acoustic Scene Classification by Implicitly Identifying Distinct Sound Events

dl_pro

easyrec

A framework for large scale recommendation algorithms.

icassp19

Public repository for the paper "Learning Sound Event Classifiers from Web Audio with Noisy Labels"

imaging-time-series-to-improve-classification-and-imputation

Python 3.6+ (only)

langchain

🦜🔗 Build context-aware reasoning applications

leetcode

mclnn

Masked ConditionaL Neural Networks

models

Models and examples built with TensorFlow

neural-classifiers-with-few-audio

Training neural audio classifiers with few data − https://arxiv.org/abs/1810.10274

nist-grantadesignsdk-scripts

pyaudioanalysis

Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications

pytorch_ner_bilstm_cnn_crf

End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF implement in pyotrch

radicaltree

self-llm

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合**宝宝的部署教程

subspectralnet-pytorch

PyTorch Implementation of SubSpectralNet - Using Sub-Spectrogram based Convolutional Neural Networks for Acoustic Scene Classification, accepted in ICASSP 2019

undaw

Unsupervised Domain Adaptation for Acoustic Scene Classification with Wasserstein Distance

urban-sound-classification-keras

urban-sound-tagging-baseline