Speech-MASSIVE：用于 SLU 及更多任务的多语言语音数据集
Speech-MASSIVE: A Multilingual Speech Dataset for SLU and Beyond
AI总结：
本文构建涵盖12种语言的多模态多任务数据集 Speech-MASSIVE，支持 SLU 基线评测及语音转写、语言识别、语音翻译等任务。
摘要：
我们提出 Speech-MASSIVE，这是一个多语言口语理解（Spoken Language Understanding，SLU）数据集，包含 MASSIVE 文本语料库一部分内容的语音对应版本。Speech-MASSIVE 涵盖来自不同语系的 12 种语言，并从 MASSIVE 继承了意图预测和槽位填充任务的标注。我们的扩展源于大规模多语言 SLU 数据集的稀缺，以及对通用语音数据集日益增长的需求，这些数据集可用于跨语言和跨任务评估基础模型（LLM、语音编码器）。我们提供了一个多模态、多任务、多语言数据集，并报告了在各种训练场景（零样本、少样本和全量微调）下使用级联架构和端到端架构的 SLU 基线。此外，我们证明了 Speech-MASSIVE 适合作为语音转写、语言识别和语音翻译等其他任务的基准。数据集、模型和代码公开发布于：https://github.com/hlt-mt/Speech-MASSIVE
英文摘要：
We present Speech-MASSIVE, a multilingual Spoken Language Understanding (SLU) dataset comprising the speech counterpart for a portion of the MASSIVE textual corpus. Speech-MASSIVE covers 12 languages from different families and inherits from MASSIVE the annotations for the intent prediction and slot-filling tasks. Our extension is prompted by the scarcity of massively multilingual SLU datasets and the growing need for versatile speech datasets to assess foundation models (LLMs, speech encoders) across languages and tasks. We provide a multimodal, multitask, multilingual dataset and report SLU baselines using both cascaded and end-to-end architectures in various training scenarios (zero-shot, few-shot, and full fine-tune). Furthermore, we demonstrate the suitability of Speech-MASSIVE for benchmarking other tasks such as speech transcription, language identification, and speech translation. The dataset, models, and code are publicly available at: https://github.com/hlt-mt/Speech-MASSIVE
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
