AI论文

本次研究的目的是教算法如何识别不同类型的音乐。用户将提交歌曲进行分析。由于算法之前没有听过这些歌曲，因此它需要决定每首歌的独特之处。它通过通过监督学习分解歌曲来学习节奏、旋律和音高，因为程序从已经标记的例子中学习。在分类音乐时，需要考虑的一个重要因素是音乐类型，这可能相当复杂。为了确保准确性，我们使用五种不同的算法，每个算法都独立工作，对歌曲进行分析。这有助于我们更全面地了解每首歌的特点。因此，我们的目标是正确识别每个提交的文件的音高。分析完成时，结果使用绘图工具呈现，使用户容易理解并提供反馈。

The aim of this study is to teach an algorithm how to recognize different types of music. Users will submit songs for analysis. Since the algorithm hasn’t heard these songs before, it needs to figure out what makes each song unique. It does this by breaking down the songs into different parts and studying things like rhythm, melody, and tone via supervised learning because the program learns from examples that are already labelled. One important thing to consider when classifying music is its genre, which can be quite complex. To ensure accuracy, we use five different algorithms, each working independently, to analyze the songs. This helps us get a more complete understanding of each song’s characteristics. Therefore, our goal is to correctly identify the genre of each submitted song. Once the analysis is done, the results are presented using a graphing tool, making it easy for users to understand and provide feedback.

https://arxiv.org/abs/2405.17413

https://arxiv.org/pdf/2405.17413.pdf