MS-SNSD

MS-SNSD是由微软公司创建的一个可扩展的噪声语音数据集，旨在支持深度学习在语音增强领域的研究。该数据集通过数据增强技术，可以根据需要扩展到任意大小，涵盖多种说话人、噪声类型和信噪比水平。数据集内容丰富，包括来自不同来源的噪声和清晰的语音样本，通过精心挑选和处理，确保数据质量。创建过程中，使用了多种技术和工具，如数据增强和在线主观测试框架，以确保数据集的实用性和准确性。该数据集主要应用于语音增强算法的开发和评估，旨在解决VoIP和PSTN通话中的背景噪声问题，提高语音通信质量。

MS-SNSD is a scalable noisy speech dataset developed by Microsoft Corporation, which aims to support research on deep learning applications in the field of speech enhancement. This dataset can be scaled to any desired size via data augmentation techniques, covering multiple speakers, noise types and signal-to-noise ratio (SNR) levels. It features rich content, including noise and clean speech samples from diverse sources, with data quality ensured through careful selection and processing. During its creation, various technologies and tools were employed, such as data augmentation and an online subjective test framework, to guarantee the practicality and accuracy of the dataset. This dataset is primarily used for the development and evaluation of speech enhancement algorithms, aiming to address background noise issues in VoIP and PSTN calls and improve the quality of voice communications.

搜集汇总

背景与挑战

背景概述

MS-SNSD是由微软创建的可扩展噪声语音数据集，通过数据增强技术支持任意规模扩展，涵盖多种说话人、噪声类型和信噪比水平，确保数据质量。该数据集专为语音增强算法的开发与评估设计，旨在解决VoIP和PSTN通话中的背景噪声问题，提升语音通信质量。