This is a growing collection of dataset I come across and I found interesting for various task related to Deep Learning.
- Classification datasets results - https://rodrigob.github.io/are_we_there_yet/build/classification_datasets_results.html
One possible way to go is transfom those sounds into images using librosa library then train a CNN on top of this.
- MLSP 2013 Bird Classification Challenge - https://www.kaggle.com/c/mlsp-2013-birds/
- Bird Audio Detection challenge - http://machine-listening.eecs.qmul.ac.uk/bird-audio-detection-challenge/
- Multi-label Bird Species Classification (NIPS 2013) - https://www.kaggle.com/c/multilabel-bird-species-classification-nips2013
- Urban Sound Dataset - https://zenodo.org/record/1206938/files/UrbanSound.tar.gz
- Freesound General Purpose Audio Tagging Challenge - https://www.kaggle.com/c/freesound-audio-tagging/data
It can be anything: planes, machineray, animals, cities, planets/stars, pokemons, Marvel characters, video games, fruits, road signs.
- DIUx xView 2018 Detection Challenge OBJECTS IN CONTEXT IN OVERHEAD IMAGERY - link
- Challenges in Representation Learning: Facial Expression Recognition Challenge - link
- The Karolinska Directed Emotional Faces (KDEF) - EmotionLab Download Page Direct Links
- Birds classification - kaggle Macaulay Library Cornell University Lab of Ornithology
- Flowers classification - http://www.robots.ox.ac.uk/~vgg/data/flowers/
- 10 Monkey species - https://www.kaggle.com/slothkong/10-monkey-species
- Plants Dataset - https://www.imageclef.org/2013/plant
- Timeseries Classification dataset - link
- Visual Object Classes Challenge 2012 (VOC2012) - link
- Cars Dataset - link
- Image data set for alphabets in the American Sign Language - code link
- Fingerprint Verification Challenge - http://bias.csr.unibo.it/fvc2000/
- Pokemon images dataset - https://www.kaggle.com/kvpratama/pokemon-images-dataset
- Pokemon Database - https://pokemondb.net/pokedex/all
- Composers classification with ResNet on spectrogram images - link
- Text to image - link
- Using deep learning to listen for whales - link
- Whale FM: recordings of Orca and Pilot Whale - link
- The Marinexplore and Cornell University Whale Detection Challenge - link #sound
- Right Whale Recognition - link #image
- Watkins Marine Mammal Sound Database - link #sound
- NOAA Northest Fisheries Science Center - link
- Arabic scientific manuscripts - link
- Centre for Pattern Recognition and Machine Intelligence - link
- Arabic Natural Language Processing at Stanford - link
- a collection of datasets - link