This article shares the author’s surprising discovery that a three-year-old accompaniment separation model performs far beyond expectations when using AI audio synthesis tools. The author compared it with mainstream tools like Kuaishou and Jianying, finding that this older model excels in separating vocals and accompaniment with a perfection rate of over 90%. The article provides audio samples of the actual separation效果, demonstrating the technology’s outstanding performance when handling complex musical works. This discovery indicates that AI audio processing technology has made significant progress over the past few years, with some early models remaining competitive for specific tasks. For professionals and enthusiasts in music production, audio editing, and related fields, this model offers an efficient and high-quality solution for accompaniment separation.
Original Link:Linux.do
最新评论
I don't think the title of your article matches the content lol. Just kidding, mainly because I had some doubts after reading the article.
这个AI状态研究很深入,数据量也很大,很有参考价值。
我偶尔阅读 这个旅游网站。激励人心查看路线。
文章内容很有深度,AI模型的发展趋势值得关注。
内容丰富,对未来趋势分析得挺到位的。
Thank you for your sharing. I am worried that I lack creative ideas. It is your article that makes me full of hope. Thank you. But, I have a question, can you help me?
光纤技术真厉害,文章解析得挺透彻的。
文章内容很实用,想了解更多相关技巧。