Recent singing-voice-synthesis (SVS) methods have achieved remarkable audio
quality and naturalness, yet they lack the capability to control the style
attributes of the synthesized singing explicitly. We propose Prompt-Singer, the
first SVS method that enables attribute controlling on singer gender, vocal
range and volume with natural language. We adopt a model architecture based on
a decoder-only transformer with a multi-scale hierarchy, and design a
range-melody decoupled pitch representation that enables text-conditioned vocal
range control while keeping melodic accuracy. Furthermore, we explore various
experiment settings, including different types of text representations, text
encoder fine-tuning, and introducing speech data to alleviate data scarcity,
aiming to facilitate further research. Experiments show that our model achieves
favorable controlling ability and audio quality. Audio samples are available at
this http URL .

提供了一种新的歌声合成方法 Prompt-Singer，使得合成歌声能够通过自然语言明确地控制歌手的性别、音域和音量，并使用基于解码器的 transformer 模型和多尺度层次结构设计了分离音域旋律的音高表示方法以保持旋律准确性，同时，对不同类型的文本表示、文本编码器微调和引入语音数据以减轻数据稀缺问题等不同实验设置进行了探索，旨在促进进一步的研究，实验证明该模型具有良好的控制能力和音频质量。