Datasets:
Dataset Card for otoSpeech-HQ-full-duplex-samples: Full-Duplex Conversational Speech Dataset Samples
Dataset Summary
otoSpeech-HQ-full-duplex-samples is a curated collection of high-quality full-duplex conversational speech samples designed for commercial and production-oriented use.
This repository is derived from a private subset of otoSpeech and features carefully selected English two-speaker conversations with enhanced audio quality. The samples are intended for evaluation, demonstration, prototyping, and other business-facing applications that require natural, high-fidelity conversational audio.
Each sample includes 44.1 kHz, channel-separated audio, preserving realistic full-duplex interaction such as overlaps, interruptions, laughter, and natural turn-taking. The audio has been selected from high-quality sessions and processed with noise reduction and speech enhancement to provide cleaner listening conditions while maintaining conversational authenticity.
The recordings reflect a range of real-world environments, microphone characteristics, and speaking styles, offering commercially relevant examples of natural spoken dialogue.
This repository is intended as a sample set for users who want convenient access to premium-quality conversational audio from the otoSpeech collection.
Languages
- English (
en)
Dataset Metadata
Please refer to the otoSpeech-full-duplex-280h repository for details: https://huggingface.co/datasets/otoearth/otoSpeech-full-duplex-280h
Contact
The data released this time is a part of the dataset we possess. If you would like the remaining dataset or a dataset with special requirements, please contact us at the address below.
Website: https://oto.earth Email: consome@oto.earth
We can acquire various types of data according to your requests. For example:
- Full-duplex conversation audio with 3 or more speakers
- Full-duplex conversation audio with specific accents
- Full-duplex conversation audio during gaming
- Full-duplex conversation audio in specific situations (e.g., customer support, doctor-patient conversations)
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