A Survey on Recent Deep Learning-driven Singing Voice Synthesis Systems

By Yin-Ping Cho, Fu-Rong Yang, Yung-Chuan Chang, Ching-Ting Cheng, Xiao-Han Wang, Yi-Wen Liu. 2021

21 citations recorded by the source corpus.

Singing voice synthesis (SVS) is a task that aims to generate audio signals according to musical scores and lyrics. With its multifaceted nature concerning music and language, producing singing voices indistinguishable from that of human singers has always remained an unfulfilled pursuit. Nonetheless, the advancements of deep learning techniques have brought about a substantial leap in the quality and naturalness of synthesized singing voice. This paper aims to review some of the state-of-the-art deep learning-driven SVS systems. We intend to summarize their deployed model architectures and identify the strengths and limitations for each of the introduced systems. Thereby, we picture the recent advancement trajectory of this field and conclude the challenges left to be resolved both in commercial applications and academic research.

Subfields: Artificial Intelligence, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Dongchao Yang
2. Rongjie Huang
3. Jiatong Shi
4. Jiang Bian
5. Xuejiao Tan
6. Songxiang Liu
7. Xuankai Chang

In Signal Processing

1. Dongchao Yang
2. Rongjie Huang
3. Jiatong Shi
4. Jiang Bian
5. Xuejiao Tan
6. Songxiang Liu
7. Xuankai Chang

Citations in the corpus

• UniAudio: An Audio Foundation Model Toward Universal Audio Generation (2023, background): “Prior works on audio generation tasks are commonly task-specific: their designs heavily leverage domain knowledge and their usage is restricted to fixed setups (Tan et al., 2021; Luo & Mesgarani, 2019; Zmolikova et al., 2023; Huang et al., 2021b; Cho et al., 2021).”
• M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus (2022, unknown): “…and the continuous breakthroughs in TTS techniques [47; 23; 52; 37; 35; 36; 18], singing voice synthesis [45; 21; 14; 5; 38; 2; 27; 40; 9; 13; 10; 51; 17; 8; 43; 1; 22; 48; 54; 41; 19; 56; 53; 25] and its related tasks (e.g., SVC [33; 42; 24; 46; 55]) have received extensive attention in…”