RIYE Audio Dataset: A Multidialectal Speech Corpus for Low-Resource Language Processing

This dataset consists of a curated collection of high-fidelity, field-recorded audio samples developed under the Digiculture RIYE Project's ethnographic survey framework. Created to bridge the digital divide for under-resourced languages, this corpus captures diverse regional speech patterns, unique tonal variations, and distinct phonetic markers essential for localised speech research.

The dataset is designed to support a wide array of machine learning, signal processing, and computational linguistics tasks. Because the audio is formatted for clean feature engineering, it serves as an ideal baseline for researchers developing neural networks, automatic speech recognition (ASR) engines, and lightweight audio classification systems optimised for edge deployment.

本数据集为经精心遴选的高保真实地录制音频样本合集，其开发依托Digiculture RIYE项目的民族志调研框架。本语料库旨在弥合低资源语言群体面临的数字鸿沟，收录了多样化的区域语音模式、独特的声调变体以及支撑本地化语音研究所需的特色语音标记。

本数据集可支撑机器学习、信号处理及计算语言学领域的各类研究任务。由于该音频格式经过优化，便于开展标准化特征工程，因此可为研发神经网络、自动语音识别（ASR）引擎以及面向边缘部署优化的轻量级音频分类系统的研究人员提供理想的基准数据集。