A large emotional voice conversion (EVC) dataset curated from spontaneous, in-the-wild podcast speech as part of the NaturalVoices project in collaboration with 🤗MSP Lab at CMU LTI. This release provides the emotion balanced subset of the NaturalVoices 870-hour VC dataset and intended for training and evaluating emotion-aware voice conversion systems but not limited to VC tasks.

📄 Paper: NaturalVoices: A Large-Scale, Spontaneous and Emotional Podcast Dataset for Voice Conversion — https://arxiv.org/abs/2511.00256 \
🧺 Dataset collection (related subsets, e.g., 10% of data & emotional VC): https://huggingface.co/collections/JHU-SmileLab/naturalvoices-voice-conversion-datasets \
The extensive (unfiltered) NaturalVoices dataset and the code for the data collection & curation pipeline: https://github.com/Lab-MSP/NaturalVoices

Dataset Summary

NaturalVoices VC compiles real-life, expressive podcast speech and provides automatic annotations designed for VC research (e.g., emotion attributes, speaker identity, speech quality, transcripts). The broader NaturalVoices corpus contains thousands of hours of podcast speech; this repository hosts the EVC subset.

What’s in this repo

~370 hours of podcast speech tailored and preprocessed for EVC.
Balanced distribution of categorical emotions (Angry, Happy, Neutral, Sad)
A wide range of speakers both manually & automatically annotated.
Annotations archive with per-utterance annotations including:
- Emotion categorical labels & dimensional attributes (valence/arousal/dominance),
- Speech quality indicators,
- Text, Gender, and Duration.

Subsets

Subset	Description	Link
NaturalVoices_VC_870h	870h of speech data curated for VC	🤗JHU-SmileLab/NaturalVoices_VC_870h
NaturalVoices_EVC	Emotion-balanced subset for Emotional Voice Conversion (EVC)	This repo
NaturalVoices_VC_01 (10%)	A smaller subset uniformly sampled from 870h (10%)	🤗JHU-SmileLab/NaturalVoices_VC_0.1

How to use

You can directly download the dataset using the following command:

huggingface-cli download JHU-SmileLab/NaturalVoices_EVC --repo-type=dataset --local-dir=YOUR_LOCAL_DIR

Streaming support will be available

Cite & Contribute

If you use this dataset, please cite the paper:

@misc{du2025naturalvoiceslargescalespontaneousemotional,
      title={NaturalVoices: A Large-Scale, Spontaneous and Emotional Podcast Dataset for Voice Conversion}, 
      author={Zongyang Du and Shreeram Suresh Chandra and Ismail Rasim Ulgen and Aurosweta Mahapatra and Ali N. Salman and Carlos Busso and Berrak Sisman},
      year={2025},
      eprint={2511.00256},
      archivePrefix={arXiv},
      primaryClass={eess.AS},
      url={https://arxiv.org/abs/2511.00256}, 
}

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Collection including JHU-SmileLab/NaturalVoices_EVC

NaturalVoices - Voice Conversion Datasets

Collection

This is a collaborative work of JHU Smile Lab and CMU MSP Lab. Please cite https://arxiv.org/abs/2511.00256 • 5 items • Updated 1 day ago • 4