Ying-Hui Lai

1.8k total citations
62 papers, 1.2k citations indexed

About

Ying-Hui Lai is a scholar working on Signal Processing, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Ying-Hui Lai has authored 62 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Signal Processing, 31 papers in Cognitive Neuroscience and 18 papers in Artificial Intelligence. Recurrent topics in Ying-Hui Lai's work include Speech and Audio Processing (41 papers), Hearing Loss and Rehabilitation (28 papers) and Speech Recognition and Synthesis (17 papers). Ying-Hui Lai is often cited by papers focused on Speech and Audio Processing (41 papers), Hearing Loss and Rehabilitation (28 papers) and Speech Recognition and Synthesis (17 papers). Ying-Hui Lai collaborates with scholars based in Taiwan, United States and China. Ying-Hui Lai's co-authors include Yu Tsao, Syu‐Siang Wang, Hsiu-Wen Chang, Hsin‐Min Wang, Jen-Cheng Hou, Shih‐Hau Fang, Chi‐Te Wang, Fei Chen, Xugang Lu and Yu‐Hsuan Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of the Acoustical Society of America.

In The Last Decade

Ying-Hui Lai

60 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ying-Hui Lai Taiwan 17 650 357 328 205 164 62 1.2k
Syu‐Siang Wang Taiwan 13 501 0.8× 258 0.7× 151 0.5× 44 0.2× 132 0.8× 49 758
Yaniv Zigel Israel 19 442 0.7× 253 0.7× 231 0.7× 511 2.5× 186 1.1× 72 1.5k
Fatih Demir Türkiye 18 328 0.5× 244 0.7× 113 0.3× 40 0.2× 260 1.6× 37 1.1k
Izhak Shafran United States 21 636 1.0× 1.0k 2.8× 145 0.4× 153 0.7× 8 0.0× 73 1.7k
Roneel V. Sharan Australia 16 259 0.4× 129 0.4× 87 0.3× 155 0.8× 213 1.3× 57 767
Görkem Serbes Türkiye 16 427 0.7× 227 0.6× 34 0.1× 352 1.7× 357 2.2× 65 1.2k
Bożena Kostek Poland 18 746 1.1× 238 0.7× 373 1.1× 33 0.2× 12 0.1× 252 1.4k
Prem C. Pandey India 13 323 0.5× 113 0.3× 179 0.5× 28 0.1× 12 0.1× 90 545
Fernando Andreotti United Kingdom 16 465 0.7× 119 0.3× 1.2k 3.5× 349 1.7× 166 1.0× 27 1.9k

Countries citing papers authored by Ying-Hui Lai

Since Specialization
Citations

This map shows the geographic impact of Ying-Hui Lai'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 Ying-Hui Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying-Hui Lai more than expected).

Fields of papers citing papers by Ying-Hui Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ying-Hui Lai. 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 Ying-Hui Lai. The network helps show where Ying-Hui Lai may publish in the future.

Co-authorship network of co-authors of Ying-Hui Lai

This figure shows the co-authorship network connecting the top 25 collaborators of Ying-Hui Lai. A scholar is included among the top collaborators of Ying-Hui Lai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ying-Hui Lai. Ying-Hui Lai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lai, Ying-Hui, et al.. (2025). Turns-amplitude and power spectral analyses of surface EMG for assessing muscle fatigue and recovery during dynamic hand gripping. Computers in Biology and Medicine. 193. 110430–110430. 1 indexed citations
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Wang, Chi‐Te, et al.. (2023). Ambulatory Phonation Monitoring Using Wireless Headphones With Deep Learning Technology. IEEE Systems Journal. 17(3). 4752–4762. 2 indexed citations
4.
Hsia, Yun, et al.. (2023). Prediction of Visual Impairment in Epiretinal Membrane and Feature Analysis: A Deep Learning Approach Using Optical Coherence Tomography. Asia-Pacific Journal of Ophthalmology. 12(1). 21–28. 9 indexed citations
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Chen, Chih‐Hao, et al.. (2022). Smartphone-bundled earphones as personal sound amplification products in adults with sensorineural hearing loss. iScience. 25(12). 105436–105436. 6 indexed citations
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Lai, Ying-Hui, et al.. (2021). Phonetic posteriorgram-based voice conversion system to improve speech intelligibility of dysarthric patients. Computer Methods and Programs in Biomedicine. 215. 106602–106602. 17 indexed citations
9.
Wang, Chi‐Te, et al.. (2020). Ambulatory Phonation Monitoring With Wireless Microphones Based on the Speech Energy Envelope: Algorithm Development and Validation. JMIR mhealth and uhealth. 8(12). e16746–e16746. 2 indexed citations
10.
Chu, Yuan-Chia, et al.. (2020). A Smartphone-Based Approach to Screening for Sudden Sensorineural Hearing Loss: Cross-Sectional Validity Study. JMIR mhealth and uhealth. 8(11). e23047–e23047. 17 indexed citations
11.
Wang, Syu‐Siang, et al.. (2020). Enhancing Intelligibility of Dysarthric Speech Using Gated Convolutional-Based Voice Conversion System. 4686–4690. 16 indexed citations
12.
Chu, Yuan-Chia, Yen‐Fu Cheng, Ying-Hui Lai, et al.. (2019). A Mobile Phone–Based Approach for Hearing Screening of School-Age Children: Cross-Sectional Validation Study. JMIR mhealth and uhealth. 7(4). e12033–e12033. 35 indexed citations
13.
Lai, Ying-Hui, et al.. (2019). A joint-feature learning-based voice conversion system for dysarthric user based on deep learning technology. PubMed. 2019. 1838–1841. 5 indexed citations
14.
Liao, Wen‐Huei, et al.. (2018). IOS-based Ear Scale application for Clinical Audiology and Otology Usage. 497–498. 1 indexed citations
15.
Fang, Shih‐Hau, et al.. (2018). Detection of Pathological Voice Using Cepstrum Vectors: A Deep Learning Approach. Journal of Voice. 33(5). 634–641. 188 indexed citations
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Fu, Szu‐Wei, et al.. (2016). Joint Dictionary Learning-Based Non-Negative Matrix Factorization for Voice Conversion to Improve Speech Intelligibility After Oral Surgery. IEEE Transactions on Biomedical Engineering. 64(11). 2584–2594. 31 indexed citations
18.
Wang, Syu‐Siang, Yu Tsao, Jeih-weih Hung, et al.. (2016). Wavelet Speech Enhancement Based on Nonnegative Matrix Factorization. IEEE Signal Processing Letters. 23(8). 1101–1105. 22 indexed citations
19.
Tsao, Yu & Ying-Hui Lai. (2015). Generalized maximum a posteriori spectral amplitude estimation for speech enhancement. Speech Communication. 76. 112–126. 35 indexed citations
20.
Lai, Ying-Hui, et al.. (2013). Measuring the Long-Term SNRs of Static and Adaptive Compression Amplification Techniques for Speech in Noise. Journal of the American Academy of Audiology. 24(8). 671–683. 14 indexed citations

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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