Chien-Feng Liao

832 total citations
7 papers, 136 citations indexed

About

Chien-Feng Liao is a scholar working on Signal Processing, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Chien-Feng Liao has authored 7 papers receiving a total of 136 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Signal Processing, 5 papers in Artificial Intelligence and 2 papers in Computational Mechanics. Recurrent topics in Chien-Feng Liao's work include Speech and Audio Processing (7 papers), Speech Recognition and Synthesis (5 papers) and Music and Audio Processing (4 papers). Chien-Feng Liao is often cited by papers focused on Speech and Audio Processing (7 papers), Speech Recognition and Synthesis (5 papers) and Music and Audio Processing (4 papers). Chien-Feng Liao collaborates with scholars based in Taiwan and Japan. Chien-Feng Liao's co-authors include Yu Tsao, Szu‐Wei Fu, Shou-De Lin, Xugang Lu, Hisashi Kawai, Yen-Ju Lu, Jeih-weih Hung, Jen-Yu Liu, Chi-Chun Lee and Hsin‐Min Wang and has published in prestigious journals such as IEEE Signal Processing Letters, arXiv (Cornell University) and ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

In The Last Decade

Chien-Feng Liao

7 papers receiving 125 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chien-Feng Liao Taiwan	4	125	83	44	22	9	7	136
Jean-Marie Lemercier Germany	6	191 1.5×	141 1.7×	41 0.9×	15 0.7×	4 0.4×	14	227
Hanwu Sun Singapore	10	184 1.5×	159 1.9×	40 0.9×	18 0.8×	11 1.2×	37	228
Arvindh Krishnaswamy United States	8	163 1.3×	103 1.2×	25 0.6×	27 1.2×	6 0.7×	13	184
Deyi Tuo China	5	168 1.3×	160 1.9×	21 0.5×	9 0.4×	7 0.8×	10	200
Peter Plantinga United States	3	121 1.0×	86 1.0×	26 0.6×	16 0.7×	2 0.2×	3	130
Naoyuki Kamo Japan	10	257 2.1×	255 3.1×	48 1.1×	24 1.1×	10 1.1×	19	341
Ladislav Mošner Czechia	9	203 1.6×	186 2.2×	19 0.4×	16 0.7×	6 0.7×	25	235
Rama Doddipatla United Kingdom	10	181 1.4×	197 2.4×	26 0.6×	12 0.5×	4 0.4×	42	248
Dacheng Yin China	5	216 1.7×	144 1.7×	91 2.1×	30 1.4×	19 2.1×	8	235
Amin Fazel United States	6	107 0.9×	41 0.5×	52 1.2×	17 0.8×	11 1.2×	11	121

Countries citing papers authored by Chien-Feng Liao

Since Specialization

Citations

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

Fields of papers citing papers by Chien-Feng Liao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chien-Feng Liao. 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 Chien-Feng Liao. The network helps show where Chien-Feng Liao may publish in the future.

Co-authorship network of co-authors of Chien-Feng Liao

This figure shows the co-authorship network connecting the top 25 collaborators of Chien-Feng Liao. A scholar is included among the top collaborators of Chien-Feng Liao 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 Chien-Feng Liao. Chien-Feng Liao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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7 of 7 papers shown

1.

Liao, Chien-Feng, Jen-Yu Liu, & Yi‐Hsuan Yang. (2022). KaraSinger: Score-Free Singing Voice Synthesis with VQ-VAE Using Mel-Spectrograms. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 956–960. 1 indexed citations

2.

Fu, Szu‐Wei, Chien-Feng Liao, Kuo-Hsuan Hung, et al.. (2020). Boosting Objective Scores of Speech Enhancement Model through MetricGAN Post-Processing. arXiv (Cornell University). 2 indexed citations

3.

Lu, Yen-Ju, Chien-Feng Liao, Xugang Lu, Jeih-weih Hung, & Yu Tsao. (2020). Incorporating Broad Phonetic Information for Speech Enhancement. 2417–2421. 8 indexed citations

4.

Liao, Chien-Feng, Yu Tsao, Xugang Lu, & Hisashi Kawai. (2019). Incorporating Symbolic Sequential Modeling for Speech Enhancement. 2733–2737. 13 indexed citations

5.

Fu, Szu‐Wei, Chien-Feng Liao, Yu Tsao, & Shou-De Lin. (2019). MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement. arXiv (Cornell University). 2031–2041. 67 indexed citations

6.

Fu, Szu‐Wei, Chien-Feng Liao, & Yu Tsao. (2019). Learning With Learned Loss Function: Speech Enhancement With Quality-Net to Improve Perceptual Evaluation of Speech Quality. IEEE Signal Processing Letters. 27. 26–30. 43 indexed citations

7.

Liao, Chien-Feng, et al.. (2018). Automatic Detection of Speech Under Cold Using Discriminative Autoencoders and Strength Modeling with Multiple Sub-Dictionary Generation. 416–420. 2 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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