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Ruiqi Li

25 papers hereh-index 14751 citations29 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author19

Across the 25 of 25 papers where every author was matched, so the position is known.

fields
  • eess.AS16
  • cs.SD7
  • cs.CV1
  • cs.IR1
same name
  • Ruiqi Li — 5 papers, h 3
  • Ruiqi Li — 4 papers, h 12
  • Ruiqi Li — 3 papers, h 6
  • Ruiqi Li — 3 papers, h 3
  • Ruiqi Li — 3 papers, h 2
  • RUIQI LI — 3 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedStyleSinger: Style Transfer for Out-of-Domain Singing Voice Synthesis

18 citations · 36 across the 25 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

eess.AS2023★ 18 cited

StyleSinger: Style Transfer for Out-of-Domain Singing Voice Synthesis

Yu Zhang, Rongjie Huang, Ruiqi Li +6

Style transfer for out-of-domain (OOD) singing voice synthesis (SVS) focuses on generating high-quality singing voices with unseen styles (such as timbre, emotion, pronunciation, a…

cs.SD2023★ 1 cited

Speech-to-Speech Translation with Discrete-Unit-Based Style Transfer

Yongqi Wang, Jionghao Bai, Rongjie Huang +3

Direct speech-to-speech translation (S2ST) with discrete self-supervised representations has achieved remarkable accuracy, but is unable to preserve the speaker timbre of the sourc…

cs.IR2023

DisCover: Disentangled Music Representation Learning for Cover Song Identification

Jiahao Xun, Shengyu Zhang, Yanting Yang +7

In the field of music information retrieval (MIR), cover song identification (CSI) is a challenging task that aims to identify cover versions of a query song from a massive collect…

eess.AS2023

AlignSTS: Speech-to-Singing Conversion via Cross-Modal Alignment

Ruiqi Li, Rongjie Huang, Lichao Zhang +2

The speech-to-singing (STS) voice conversion task aims to generate singing samples corresponding to speech recordings while facing a major challenge: the alignment between the targ…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.