Mclf: A multi-grained contrastive learning framework for asr-robust spoken language understanding

Z Huang, D Chen, Z Zhu, X Cheng - Findings of the Association for …, 2023 - aclanthology.org
Enhancing the robustness towards Automatic Speech Recognition (ASR) errors is of great
importance for Spoken Language Understanding (SLU). Trending ASR-robust SLU systems …

MoE-SLU: Towards ASR-Robust Spoken Language Understanding via Mixture-of-Experts

X Cheng, Z Zhu, X Zhuang, Z Chen… - Findings of the …, 2024 - aclanthology.org
As a crucial task in the task-oriented dialogue systems, spoken language understanding
(SLU) has garnered increasing attention. However, errors from automatic speech …

Cyclical Contrastive Learning Based on Geodesic for Zero-shot Cross-lingual Spoken Language Understanding

X Cheng, Z Zhu, B Yang, X Zhuang, H Li… - Findings of the …, 2024 - aclanthology.org
Owing to the scarcity of labeled training data, Spoken Language Understanding (SLU) is still
a challenging task in low-resource languages. Therefore, zero-shot cross-lingual SLU …

Feature-augmented Machine Reading Comprehension with Auxiliary Tasks

Y Xie - arXiv preprint arXiv:2211.09438, 2022 - arxiv.org
While most successful approaches for machine reading comprehension rely on single
training objective, it is assumed that the encoder layer can learn great representation …

[PDF][PDF] I Learned Error, I Can Fix It!: A Detector-Corrector Structure for ASR Error Calibration

HY Yeen, MJ Kim, MW Koo - isca-archive.org
Speech recognition technology has improved recently. However, in the context of spoken
language understanding (SLU), containing automatic speech recognition (ASR) errors …