Although Singing Voice Synthesis (SVS) has made great strides with Text-to-Speech (TTS) techniques, multilingual singing voice modeling remains relatively unexplored. This paper presents BiSinger, a bilingual pop SVS system for English and Chinese Mandarin. Current systems require separate models per language and cannot accurately represent both Chinese and English, hindering code-switch SVS. To address this gap, we design a shared representation between Chinese and English singing voices, achieved by using the CMU dictionary with mapping rules. We fuse monolingual singing datasets with open-source singing voice conversion techniques to generate bilingual singing voices while also exploring the potential use of bilingual speech data. Experiments affirm that our language-independent representation and incorporation of related datasets enable a single model with enhanced performance in English and code-switch SVS while maintaining Chinese song performance. Audio samples are available at https://bisinger-svs.github.io.

翻译：尽管歌唱语音合成（SVS）借助文本转语音（TTS）技术取得了显著进展，但多语言歌唱声音建模仍相对未被充分探索。本文提出了BiSinger，一个用于英语和汉语普通话的双语流行音乐SVS系统。当前系统需要为每种语言单独训练模型，且无法准确表示中文和英文，这阻碍了代码切换SVS的发展。为解决这一不足，我们通过使用带有映射规则的CMU词典，设计了一种中英文歌唱声音的共享表示。我们融合单语歌唱数据集与开源歌唱声音转换技术，生成双语歌唱声音，同时探索了双语语音数据的潜在应用。实验证实，我们的语言无关表示及对相关数据集的整合，使得单一模型在英语和代码切换SVS中性能提升，同时保持中文歌曲性能。音频样本可在https://bisinger-svs.github.io获取。