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J. Sung

16 papers hereh-index 9258 citations34 works total

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

author position
  • middle author15
  • last author1

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.SD13
  • eess.AS3
same name
  • J. Sung — 11 papers, h 28
  • J. Sung — 9 papers, h 28
  • J. Sung — 3 papers, h 22
  • J. Sung — 3 papers, h 2
  • J. Sung — 2 papers, h 3
  • J. Sung — 1 paper, h 13

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

most citedSOMOS: The Samsung Open MOS Dataset for the Evaluation of Neural Text-to-Speech Synthesis

27 citations · 121 across the 16 of their papers we have counts for

collaborators
Showing eess.ASShow all

3 papers · 1 filter

eess.AS2022★ 3 cited

Karaoker: Alignment-free singing voice synthesis with speech training data

Panos Kakoulidis, Nikolaos Ellinas, Georgios Vamvoukakis +5

Existing singing voice synthesis models (SVS) are usually trained on singing data and depend on either error-prone time-alignment and duration features or explicit music score info…

eess.AS2022

Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge

Sangjun Park, Kihyun Choo, Joohyung Lee +3

Text-to-Speech (TTS) services that run on edge devices have many advantages compared to cloud TTS, e.g., latency and privacy issues. However, neural vocoders with a low complexity…

eess.AS2021★ 26 cited

Expressive Text-to-Speech using Style Tag

Minchan Kim, Sung Jun Cheon, Byoung Jin Choi +2

As recent text-to-speech (TTS) systems have been rapidly improved in speech quality and generation speed, many researchers now focus on a more challenging issue: expressive TTS. To…

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