Omkar2118/datasets huggingface dataset:
AdobeIndoorNav

**AdobeIndoorNav** is a dataset collected in real-world to facilitate the research in DRL based visual navigation. The dataset includes 3D reconstruction for real-world scenes as well as densely captured real 2D images from the scenes. It provides high-quality visual inputs with real-world scene complexity to the robot at dense grid locations.

Introducing paper: The AdobeIndoorNav Dataset: Towards Deep Reinforcement Learning based Real-world Indoor Robot Visual Navigation
nicolingua-0003-west-african-radio-corpus
Full name: West African Radio Corpus

This dataset contains 17,090 audio clips of length 30 seconds sampled from archives collected from 6 Guinean radio stations. The broadcasts consist of news and various radio shows in languages including French, Guerze, Koniaka, Kissi, Kono, Maninka, Mano, Pular, Susu, and Toma. Some radio shows include phone calls, background and foreground music, and various noise types. We collected this dataset for the purpose of unsupervised speech representation learning. A validation set of 300 tagged audio clips is also included.
nicolingua-0004-west-african-va-asr-corpus
Full name: West African Virtual Assistant Speech Recognition Corpus

This dataset contains 10,083 recorded utterances in French, Maninka, Pular and Susu from 49 speakers (16 female and 33 male) ranging from 5 to 76 years old on a variety of devices.

Please see our paper for more details on this dataset. Additional resources can be found in the following git repository: https://github.com/mdoumbouya/nicolingua