论文标题
探索校准歌词信息的歌声分离
Exploring Aligned Lyrics-Informed Singing Voice Separation
论文作者
论文摘要
在本文中，我们提出了一种利用对齐歌词作为其他信息来提高歌声分离的性能的方法。我们已经将基于高速公路网络的歌词编码器结合到了开放式分离网络中，并表明，经过对齐歌词训练的模型确实会比未通知的模型更好地表现出更好的性能。现在的问题是，性能的提高实际上是由于语音内容是否存在于知情的歌词中。为此，我们通过观察模型不正确的歌词时的性能变化来研究多方面方式的性能提高。实验结果表明，该模型不仅可以使用声音活动信息，还可以使用对齐歌词中的语音内容。
In this paper, we propose a method of utilizing aligned lyrics as additional information to improve the performance of singing voice separation. We have combined the highway network-based lyrics encoder into Open-unmix separation network and show that the model trained with the aligned lyrics indeed results in a better performance than the model that was not informed. The question now remains whether the increase of performance is actually due to the phonetic contents that lie in the informed aligned lyrics or not. To this end, we investigated the source of performance increase in multifaceted ways by observing the change of performance when incorrect lyrics were given to the model. Experiment results show that the model can use not only just vocal activity information but also the phonetic contents from the aligned lyrics.
