datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
VaaniVAANI is an India-representative multi-modal multi-lingual dataset.
The current version (phase 1- 80 districts, phase 2- 85 districts) contains ~31278 hours of spontaenous,image-prompted speech by 156K speakers across 165 districts, talking about 288K images covering 105 languages.
From this audio data, 2,122 hours of transcribed data(text) is available, spanning almost evenly across the 165 districts.
Project Vaani, by IISc, Bangalore and ARTPARK, is capturing the true diversity of India’s… See the full description on the dataset page: https://huggingface.co/datasets/ARTPARK-IISc/Vaani.ASMR-Archive-Processed
ASMR-Archive-Processed (WIP)
Update (2026-04-03): This dataset has reached the Hugging Face Public Storage Limit. After contacting support, we were informed that the only option is to pay for a storage expansion. Consequently, updates to this dataset are now suspended.
Work in Progress — expect breaking changes while the pipeline and data layout stabilize.
This dataset contains ASMR audio data sourced from DeliberatorArchiver/asmr-archive-data-01 and… See the full description on the dataset page: https://huggingface.co/datasets/OmniAICreator/ASMR-Archive-Processed.NEXUS-temporal_hierarchical_multi-modal
NEXUS: Neural Evolution for eXtensible Universal Semantics Dataset
(Temporal Multimodal Slices)
This dataset is a multi-modal, hierarchical, temporal representation derived from HuggingFaceFV/finevideo. It is designed for streaming training where the primary unit is a 10 ms "slice" that aggregates upward into moments (100 ms), seconds (1 s), experiences (10 s), and minutes (60 s).
It is meant to represent an extensible stream of "experience" as there are… See the full description on the dataset page: https://huggingface.co/datasets/Ardea/NEXUS-temporal_hierarchical_multi-modal.Vaani-Benchmark-V1.0
Vaani-Benchmark-V1.0
A curated ASR evaluation set drawn from the Vaani project. This benchmark contains 5,050 audio segments from 1,103 speakers across 104 Indian districts, each with three independent human transcriptions.
Evaluation Toolkit
A standalone toolkit implementing this benchmark's scoring methodology, plus
Latin-script normalization for code-switched predictions and one-command
publishing of results to a model's HF card, is available at… See the full description on the dataset page: https://huggingface.co/datasets/ARTPARK-IISc/Vaani-Benchmark-V1.0.Vaani-Atypical-Speech-CorpusProject Euphonia is a public initiative led by Google that aims to improve Automatic Speech Recognition (ASR) for individuals with atypical speech. To date, most of Project Euphonia’s work has focused on English, resulting in outcomes such as the Android application Project Relate, which generates personalized speech recognition models in English.
In recent years, the project has expanded its data collection efforts to additional languages, including French, Spanish, Japanese, and Hindi.
The… See the full description on the dataset page: https://huggingface.co/datasets/ARTPARK-IISc/Vaani-Atypical-Speech-Corpus.