Che-Wei Huang

563 total citations
22 papers, 367 citations indexed

About

Che-Wei Huang is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Che-Wei Huang has authored 22 papers receiving a total of 367 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 10 papers in Signal Processing and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Che-Wei Huang's work include Speech and Audio Processing (6 papers), Music and Audio Processing (6 papers) and Speech Recognition and Synthesis (6 papers). Che-Wei Huang is often cited by papers focused on Speech and Audio Processing (6 papers), Music and Audio Processing (6 papers) and Speech Recognition and Synthesis (6 papers). Che-Wei Huang collaborates with scholars based in United States, Taiwan and Australia. Che-Wei Huang's co-authors include Shrikanth Narayanan, Josh Jia-Ching Ying, Vincent S. Tseng, Kuan-Ta Chen, Roland Maas, Chih‐Ting Lin, Zac E. Imel, Panayiotis Georgiou, David C. Atkins and Sri Harish Mallidi and has published in prestigious journals such as Sensors, IEEE Sensors Journal and IEEE Transactions on Biomedical Circuits and Systems.

In The Last Decade

Che-Wei Huang

22 papers receiving 343 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Che-Wei Huang United States	10	178	143	125	41	40	22	367
Değer Ayata Türkiye	8	117 0.7×	79 0.6×	212 1.7×	86 2.1×	15 0.4×	11	439
Nobuo Sato Japan	9	59 0.3×	86 0.6×	91 0.7×	54 1.3×	21 0.5×	27	319
Carmén García Mateo Spain	12	311 1.7×	279 2.0×	98 0.8×	108 2.6×	14 0.3×	86	525
Laura Docío-Fernández Spain	12	243 1.4×	169 1.2×	98 0.8×	103 2.5×	7 0.2×	63	418
Wei Tao China	8	166 0.9×	60 0.4×	186 1.5×	101 2.5×	13 0.3×	10	445
C. Longworth United Kingdom	4	84 0.5×	72 0.5×	86 0.7×	117 2.9×	62 1.6×	9	371
Kun-Yi Huang Taiwan	10	185 1.0×	81 0.6×	210 1.7×	69 1.7×	8 0.2×	25	420
Tim Polzehl Germany	14	293 1.6×	214 1.5×	255 2.0×	91 2.2×	20 0.5×	50	568
Syaheerah Lebai Lutfi Malaysia	10	106 0.6×	76 0.5×	75 0.6×	171 4.2×	17 0.4×	42	342
Georgios Rizos United Kingdom	10	173 1.0×	92 0.6×	66 0.5×	38 0.9×	7 0.2×	21	305

Countries citing papers authored by Che-Wei Huang

Since Specialization

Citations

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

Fields of papers citing papers by Che-Wei Huang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Che-Wei Huang. 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 Che-Wei Huang. The network helps show where Che-Wei Huang may publish in the future.

Co-authorship network of co-authors of Che-Wei Huang

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

All Works

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20 of 20 papers shown

Huang, Che-Wei, et al.. (2022). Incremental User Embedding Modeling for Personalized Text Classification. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7832–7836. 3 indexed citations

Huang, Che-Wei, et al.. (2021). Streaming ResLSTM with Causal Mean Aggregation for Device-Directed Utterance Detection. 659–664. 4 indexed citations

Huang, Che-Wei, et al.. (2021). Design of Industrial Control System Secure Communication Using Moving Target Defense with Legacy Infrastructure. Sensors and Materials. 33(10). 3415–3415. 1 indexed citations

Guo, Jinxi, Jasha Droppo, Maarten Van Segbroeck, et al.. (2020). Efficient Minimum Word Error Rate Training of RNN-Transducer for End-to-End Speech Recognition. 2807–2811. 27 indexed citations

Huang, Che-Wei, Roland Maas, Sri Harish Mallidi, & Björn Hoffmeister. (2019). A Study for Improving Device-Directed Speech Detection Toward Frictionless Human-Machine Interaction. 3342–3346. 16 indexed citations

Ying, Josh Jia-Ching, Ji Zhang, Che-Wei Huang, Kuan-Ta Chen, & Vincent S. Tseng. (2018). FrauDetector ⁺. ACM Transactions on Knowledge Discovery from Data. 12(6). 1–35. 9 indexed citations

Huang, Che-Wei & Shrikanth Narayanan. (2018). Stochastic Shake-Shake Regularization for Affective Learning from Speech. 3658–3662. 2 indexed citations

Huang, Che-Wei & Shrikanth Narayanan. (2017). Deep convolutional recurrent neural network with attention mechanism for robust speech emotion recognition. 583–588. 92 indexed citations

Huang, Che-Wei, et al.. (2016). A technology prototype system for rating therapist empathy from audio recordings in addiction counseling. PeerJ Computer Science. 2. e59–e59. 39 indexed citations

10.

Huang, Che-Wei & Shrikanth Narayanan. (2016). Attention Assisted Discovery of Sub-Utterance Structure in Speech Emotion Recognition. 1387–1391. 64 indexed citations

11.

Ying, Josh Jia-Ching, Zhang Ji, Che-Wei Huang, Kuan-Ta Chen, & Vincent S. Tseng. (2016). PFrauDetector: A Parallelized Graph Mining Approach for Efficient Fraudulent Phone Call Detection. University of Southern Queensland ePrints (University of Southern Queensland). 1059–1066. 3 indexed citations

12.

Huang, Che-Wei & Shrikanth Narayanan. (2016). Comparison of feature-level and kernel-level data fusion methods in multi-sensory fall detection. 1–6. 3 indexed citations

13.

Huang, Che-Wei & Shrikanth Narayanan. (2016). Comparison of feature-level and kernel-level data fusion methods in multi-sensory fall detection. 5. 1–6. 4 indexed citations

14.

Kumar, Naveen, et al.. (2016). Novel affective features for multiscale prediction of emotion in music. 1–5. 2 indexed citations

15.

Huang, Che-Wei & Shrikanth Narayanan. (2016). Flow of Renyi information in deep neural networks. 1–6. 4 indexed citations

16.

Guha, Tanaya, et al.. (2015). Gender Representation in Cinematic Content. Warwick Research Archive Portal (University of Warwick). 31–34. 15 indexed citations

17.

Huang, Che-Wei, Bo Xiao, Panayiotis Georgiou, & Shrikanth Narayanan. (2014). Unsupervised speaker diarization using riemannian manifold clustering. 567–571. 3 indexed citations

18.

Huang, Yujie, Che-Wei Huang, Tsung‐Hsien Lin, et al.. (2013). A CMOS Cantilever-Based Label-Free DNA SoC With Improved Sensitivity for Hepatitis B Virus Detection. IEEE Transactions on Biomedical Circuits and Systems. 7(6). 820–831. 25 indexed citations

19.

Huang, Che-Wei, Yujie Huang, Shey‐Shi Lu, & Chih‐Ting Lin. (2012). A Fully Integrated Humidity Sensor System-on-Chip Fabricated by Micro-Stamping Technology. Sensors. 12(9). 11592–11600. 6 indexed citations

20.

Lin, Chih‐Ting & Che-Wei Huang. (2010). Low-Power and High-Sensitivity Humidity Sensor Using Fe-Al-Polyaniline Blends. IEEE Sensors Journal. 10(6). 1142–1146. 9 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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