Li-Chia Yang

1.3k citations
11 papers · 519 · h-index 8

Impact in

Papers in

Li-Chia Yang

11 papers receiving 495 citations

Peers

Li-Chia Yang
Comparison fields: 5 of 62
  • Signal Processing 379
  • Computer Vision and Pattern Recognition 351
  • Cognitive Neuroscience 169
  • Music 22
  • Artificial Intelligence 125
Replace Wen-Yi Hsiao with:
Wen-Yi Hsiao Taiwan
Luís Gustavo Martins Portugal
Cheng-Zhi Anna Huang United States
Barry Vercoe United States
Nicholas J. Bryan United States
Andreas F. Ehmann United States
Olivier Delerue France
Zekeriya TÜFEKCİ Türkiye
Ryuichi Oka Japan
David Meredith Denmark
Li-Chia Yang relative to Wen-Yi Hsiao Taiwan Wen-Yi Hsiao's profile →
Citations per field
00.5×1.5×2.2×
Wen-Yi Hsiao · 1×
Citations per year

Countries citing papers authored by Li-Chia Yang

Since Specialization
Citations

This map shows the geographic impact of Li-Chia Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Li-Chia Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li-Chia Yang more than expected).

Fields of papers citing papers by Li-Chia Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li-Chia Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Li-Chia Yang. The network helps show where Li-Chia Yang may publish in the future.

Co-authors

The 14 scholars most cited alongside Li-Chia Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Li-Chia Yang Line = papers co-authored together Li-Chia Yang links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2018268
2 201888
3 202076
4 201719
5 201719
6
MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation using 1D and 2D Conditions.
201715
7
MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks
201714
8 202312
9 20175
10 20222
11 20091

About Li-Chia Yang

Li-Chia Yang is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Information Systems, having authored 11 papers that have together received 519 indexed citations. Recurring topics across this work include Music and Audio Processing (8 papers), Music Technology and Sound Studies (6 papers), Speech and Audio Processing (3 papers), Neuroscience and Music Perception (2 papers), Speech Recognition and Synthesis (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Electrostatics and Colloid Interactions (1 paper) and Microfluidic and Bio-sensing Technologies (1 paper). The work is most often cited by research in Signal Processing (379 citations), Computer Vision and Pattern Recognition (351 citations), Cognitive Neuroscience (169 citations), Music (22 citations) and Artificial Intelligence (125 citations). Li-Chia Yang has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Yi‐Hsuan Yang, Wen-Yi Hsiao, Hao‐Wen Dong, Alexander Lerch, Szu-Yu Chou, Matthew Mattina, Paul N. Whatmough, Carl Jensen, Jen-Yu Liu and Yi‐An Chen. Their work appears in journals such as Neural Computing and Applications, Electrophoresis, arXiv (Cornell University), Interspeech 2022 and Zenodo (CERN European Organization for Nuclear Research).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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