Urban sound classification using Deep Learning

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

Urban sound source tagging from an aggregation of four second noisy audio clips via 1D and 2D CNN (Xception)

Sound Classification using Neural Networks

Spectrogram for UrbanSound8K audio dataset

Sound classification on Urban Sound Dataset

Set of 1D CNN models to classify sound clips from the Urban Sound Classification dataset using Keras and Librosa

Classification of urban sounds such as air conditioner, jackhammer, drilling, siren, street music, engine idling and children playing by using Mel-frequency Cepstral Coefficients (MFCCs) as audio feature and CNN algorithm.

Urban Sound Challenge project

consist of python scripts, having various models for urban sound classification on UrbanSound8K dataset based on http://aqibsaeed.github.io/2016-09-03-urban-sound-classification-part-1/

Classifying Sounds

My Urban Sound Challenge classification

A deep learning classifier for urban sounds using the EfficientNet network

Waveplot for UrbanSound8K audio dataset

Web app for urban sound classification

In this project, I implemented Convolutional Neural Networks on images of melspectrogram of sound files.

The goal of this project is to obtain a classifier that can automatically classify environmental sounds according to their category. This can be implemented on both transport vehicles and wearable devices to improve road safety.

A CNN model trained using spectrograms of urban sounds

Urban Sound Classification

[SCH졸업논문] 위급한 상황의 소리를 딥러닝으로 인식하여 알려줍니다