HumTrans：一个用于哼唱旋律转录的新型开源数据集及其扩展应用
HumTrans: A Novel Open-Source Dataset for Humming Melody Transcription and Beyond
AI总结：
本文介绍公开的HumTrans哼唱旋律转录数据集，含500首作品、1000个片段、56.22小时音频，由10名音乐学生录制，支持转录及音乐生成等下游任务。
摘要：
本文介绍了HumTrans数据集，该数据集公开可用，主要设计用于哼唱旋律转录。该数据集还可作为哼唱旋律音乐生成等下游任务的基础。它包含500首不同流派和语言的作品，每首作品被划分为多个片段。总计，该数据集包含1000个音乐片段。为了收集这个哼唱数据集，我们雇佣了10名大学生，他们要么是音乐专业，要么精通至少一种乐器。他们每个人使用我们设计的网站提供的网络录音界面，对每个片段哼唱两次。哼唱录音的采样频率为44,100赫兹。在哼唱过程中，主界面提供乐谱供学生参考，同时播放旋律音频以帮助捕捉旋律和节奏。该数据集包含约56.22小时的音频，是迄今为止已知最大的哼唱数据集。该数据集将在Hugging Face上发布，我们将提供一个包含基线结果和评估代码的GitHub仓库。
英文摘要：
This paper introduces the HumTrans dataset, which is publicly available and primarily designed for humming melody transcription. The dataset can also serve as a foundation for downstream tasks such as humming melody based music generation. It consists of 500 musical compositions of different genres and languages, with each composition divided into multiple segments. In total, the dataset comprises 1000 music segments. To collect this humming dataset, we employed 10 college students, all of whom are either music majors or proficient in playing at least one musical instrument. Each of them hummed every segment twice using the web recording interface provided by our designed website. The humming recordings were sampled at a frequency of 44,100 Hz. During the humming session, the main interface provides a musical score for students to reference, with the melody audio playing simultaneously to aid in capturing both melody and rhythm. The dataset encompasses approximately 56.22 hours of audio, making it the largest known humming dataset to date. The dataset will be released on Hugging Face, and we will provide a GitHub repository containing baseline results and evaluation codes.
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。
