DeepASMR-NSpeech

A Fine-Grained Benchmark for Non-Speech ASMR Generation

73,829 ten-second clips · 202.6 hours · 37 fine-grained actions

🎧 Interactive Demo · ⌘ Code · 📄 Paper: coming soon

Dataset summary

DeepASMR-NSpeech is a non-speech ASMR audio dataset with structured Subject-Verb-Object annotations and the SVO-AQA audio question-answering benchmark. All clips are 10 seconds long and cover 37 fine-grained sound-producing actions.

Authors: Ziyi Yang, Leying Zhang, Chenda Li, and Yanmin Qian

_{Auditory Cognition and Computational Acoustics Lab
Shanghai Jiao Tong University}

Dataset statistics

Metric	Train	Test	Total / cross-split
Annotated events	12,327	1,163	13,490
Ten-second clips	72,666	1,163	73,829; 0 overlap
Duration	199.4 h	3.19 h	202.6 h

Quick start

from datasets import load_dataset

dataset = load_dataset("AudioCC-Lab/DeepASMR-NSpeech")
sample = dataset["train"][0]
print(sample["caption"], sample["audio"])

Data fields

Each Parquet row contains audio_id, embedded audio, caption, closed-set verb, open noun phrases subject and object, and anonymized creator_id.

The release also includes 431 human-validated SVO-AQA questions and a frozen 55-question audio-dependent subset. See the code repository for construction and evaluation instructions.

License and source-media rights

The structured annotations, dataset metadata, and SVO-AQA annotations that the authors are authorized to license are released under CC BY-NC 4.0.

The source media originates from third-party public videos. All associated rights remain with their respective original creators or other rights holders. Users must comply with applicable creator rights, platform terms, privacy requirements, and local law. Structured labels may contain model-assisted annotation noise.

Citation

@misc{yang2026deepasmrnspeech,
  title  = {DeepASMR-NSpeech: A Fine-Grained Benchmark for Non-Speech ASMR Generation},
  author = {Yang, Ziyi and Zhang, Leying and Li, Chenda and Qian, Yanmin},
  year   = {2026},
  note   = {Dataset and code, version 1.0.0}
}