datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.emova-alignment-7m
EMOVA-Alignment-7M
🤗 EMOVA-Models | 🤗 EMOVA-Datasets | 🤗 EMOVA-Demo
📄 Paper | 🌐 Project-Page | 💻 Github | 💻 EMOVA-Speech-Tokenizer-Github
Overview
EMOVA-Alignment-7M is a comprehensive dataset curated for omni-modal pre-training, including vision-language and speech-language alignment.
This dataset is created using open-sourced image-text pre-training datasets, OCR datasets, and 2,000 hours of ASR and TTS data.
This dataset is part of the EMOVA-Datasets… See the full description on the dataset page: https://huggingface.co/datasets/Emova-ollm/emova-alignment-7m.yodas_owsmv4🏆 News: Our OWSM v4 paper won the Best Student Paper Award at INTERSPEECH 2025!
Dataset Card for YODAS_OWSMv4
Paper: OWSM v4: Improving Open Whisper-Style Speech Models via Data Scaling and Cleaning (Best Student Paper at INTERSPEECH 2025)
Authors: Yifan Peng, Muhammad Shakeel, Yui Sudo, William Chen, Jinchuan Tian, Chyi-Jiunn Lin, Shinji Watanabe
Data Cleaning Scripts: ESPnet
Model Demo: Gradio
Dataset Description
Open Whisper-style Speech Model (OWSM)is the first… See the full description on the dataset page: https://huggingface.co/datasets/espnet/yodas_owsmv4.emova-sft-4m
EMOVA-SFT-4M
🤗 EMOVA-Models | 🤗 EMOVA-Datasets | 🤗 EMOVA-Demo
📄 Paper | 🌐 Project-Page | 💻 Github | 💻 EMOVA-Speech-Tokenizer-Github
Overview
EMOVA-SFT-4M is a comprehensive dataset curated for omni-modal instruction tuning, including textual, visual, and audio interactions. This dataset is created by gathering open-sourced multi-modal instruction datasets and synthesizing high-quality omni-modal conversation data to enhance user experience. This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Emova-ollm/emova-sft-4m.omnievalkit-dataset
OmniEvalKit Evaluation Datasets
Evaluation datasets for OmniEvalKit,
a comprehensive evaluation framework for omni-modal (audio + video + image + text) models.
Overview
Total subsets: 65
Total samples: 315,264
Total size: 620.3 GB (Parquet with embedded audio/image/video)
Subsets with embedded video: 15
Subsets requiring external video download: 2
Usage
from datasets import load_dataset
ds = load_dataset("OmniEvalKit/omnievalkit-dataset", "aishell1_test")… See the full description on the dataset page: https://huggingface.co/datasets/OmniEvalKit/omnievalkit-dataset.emova-sft-speech-231k
EMOVA-SFT-Speech-231K
🤗 EMOVA-Models | 🤗 EMOVA-Datasets | 🤗 EMOVA-Demo
📄 Paper | 🌐 Project-Page | 💻 Github | 💻 EMOVA-Speech-Tokenizer-Github
Overview
EMOVA-SFT-Speech-231K is a comprehensive dataset curated for omni-modal instruction tuning and emotional spoken dialogue. This dataset is created by converting existing text and visual instruction datasets via Text-to-Speech (TTS) tools. EMOVA-SFT-Speech-231K is part of EMOVA-Datasets collection and is used in… See the full description on the dataset page: https://huggingface.co/datasets/Emova-ollm/emova-sft-speech-231k.OmniAgentBench
OmniAgentBench Dataset
Overview
OmniAgentBench is a benchmark for evaluating multimodal agents under realistic "wild" conditions: speech input, acoustic noise, dense/scattered instructions, and multi-turn conversations. It wraps three existing agent benchmarks (MPCC, GUI Odyssey, EmbodiedBench) with speech audio, noise overlays, and wild text rewrites so that the same tasks can be evaluated under controlled input-modality variations.
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/omniagentbenchspeech/OmniAgentBench.omnievalkit-data-test
OmniEvalKit Evaluation Datasets
Evaluation datasets for OmniEvalKit,
a comprehensive evaluation framework for omni-modal (audio + video + image + text) models.
Overview
Total subsets: 89
Total samples: 353,610
Total size: 352.3 GB (Parquet with embedded audio/image, no video)
Subsets requiring video download: 42
Note: Video files are NOT embedded in the Parquet files due to size constraints.
Usage
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/xiaofff/omnievalkit-data-test.emova-sft-speech-eval
EMOVA-SFT-Speech-Eval
🤗 EMOVA-Models | 🤗 EMOVA-Datasets | 🤗 EMOVA-Demo
📄 Paper | 🌐 Project-Page | 💻 Github | 💻 EMOVA-Speech-Tokenizer-Github
Overview
EMOVA-SFT-Speech-Eval is an evaluation dataset curated for omni-modal instruction tuning and emotional spoken dialogue. This dataset is created by converting existing text and visual instruction datasets via Text-to-Speech (TTS) tools. EMOVA-SFT-Speech-Eval is part of EMOVA-Datasets collection, and the training… See the full description on the dataset page: https://huggingface.co/datasets/Emova-ollm/emova-sft-speech-eval.