灵境Umix AI模型训练数据集

Umix AI 模型训练数据集是由灵境声学构建的音频训练集。该数据集旨在支持 AI 对普通立体声信号的空间位置信息识别、声音元素解析、以及多维声场重建任务。通过该数据集，模型能够在单一音频源输入的条件下，智能识别不同声音元素在空间中的位置关系与能量分布，实现全景声、Ai听觉等应用场景的智能生成。
音乐类样本：涵盖多风格声音内容，包括流行、电子、古典、爵士、摇滚等类型。
声音元素标签：包含人声、各类乐器、动效、背景音效等标签。

采样精度：采样率 44.1kHz-192kHz，位深 16bit-32bit。
文件格式：WAV。

数据来源与清洗：
数据来源包括公开音频研究集，以及灵境声学内部录制与标注素材。所有样本均经过灵境声标准化处理，确保音质一致性和可训练性。

The Umix AI model training dataset is an audio training corpus developed by Lingjing Acoustics. This dataset aims to support AI tasks including spatial position recognition of standard stereo signals, sound element parsing, and multi-dimensional sound field reconstruction. Using this dataset, models can intelligently recognize the spatial positional relationships and energy distribution of various sound elements with a single audio source as input, thereby enabling the intelligent generation of application scenarios such as panoramic audio and AI auditory functions.

Music samples: Cover multi-style audio content spanning pop, electronic, classical, jazz, rock and other genres.

Sound element annotation tags: Include categories such as human voice, various musical instruments, foley sound effects, and background audio.

Sampling parameters: Sampling rate: 44.1kHz–192kHz, bit depth: 16bit–32bit.

File format: WAV.

Data source and cleaning: The data sources include public audio research datasets, as well as internally recorded and annotated materials from Lingjing Acoustics. All samples have been standardized by Lingjing Acoustics to ensure consistent audio quality and model trainability.

搜集汇总

背景与挑战

背景概述

该数据集是上海灵境声学技术股份有限公司申请登记的数据技术算法类产品，专注于AI模型训练应用场景。它属于数据应用场景类型，旨在支持人工智能模型的开发与优化，体现了在声学技术领域的专业应用潜力。