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arXiv · 2509.18722

LOTUSDIS: A Thai far-field meeting corpus for robust conversational ASR

Pattara Tipaksorn·Sumonmas Thatphithakkul·Vataya Chunwijitra·Kwanchiva Thangthai
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Abstract

We present LOTUSDIS, a publicly available Thai meeting corpus designed to advance far-field conversational ASR. The dataset comprises 114 hours of spontaneous, unscripted dialogue collected in 15-20 minute sessions with three participants, where overlapping speech is frequent and natural. Speech was recorded simultaneously by nine independent single-channel devices spanning six microphone types at distances from 0.12 m to 10 m, preserving the authentic effects of reverberation, noise, and device coloration without relying on microphone arrays. We provide standard train, dev, test splits and release a reproducible baseline system. We benchmarked several Whisper variants under zero-shot and fine-tuned conditions. Off-the-shelf models showed strong degradation with distance, confirming a mismatch between pre-training data and Thai far-field speech. Fine-tuning on LOTUSDIS dramatically improved robustness: a Thai Whisper baseline reduced overall WER from 64.3 to 38.3 and far-field WER from 81.6 to 49.5, with especially large gains on the most distant microphones. These results underscore the importance of distance-diverse training data for robust ASR. The corpus is available under CC-BY-SA 4.0. We also release training and evaluation scripts as a baseline system to promote reproducible research in this field.

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Pattara Tipaksorn, Sumonmas Thatphithakkul, Vataya Chunwijitra, Kwanchiva Thangthai. 2025-09-23. LOTUSDIS: A Thai far-field meeting corpus for robust conversational ASR. https://arxiv.org/abs/2509.18722

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