Duc Le

1.1k total citations
30 papers, 672 citations indexed

About

Duc Le is a scholar working on Artificial Intelligence, Signal Processing and Cognitive Neuroscience. According to data from OpenAlex, Duc Le has authored 30 papers receiving a total of 672 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 12 papers in Signal Processing and 6 papers in Cognitive Neuroscience. Recurrent topics in Duc Le's work include Speech Recognition and Synthesis (19 papers), Natural Language Processing Techniques (13 papers) and Speech and Audio Processing (9 papers). Duc Le is often cited by papers focused on Speech Recognition and Synthesis (19 papers), Natural Language Processing Techniques (13 papers) and Speech and Audio Processing (9 papers). Duc Le collaborates with scholars based in United States, Israel and Vietnam. Duc Le's co-authors include Emily Mower Provost, Michael L. Seltzer, Christian Fuegen, Julian Chan, Yangyang Shi, Ching-Feng Yeh, Jay Mahadeokar, Chunyang Wu, Carol Persad and Frank Zhang and has published in prestigious journals such as Speech Communication, IEEE/ACM Transactions on Audio Speech and Language Processing and ArXiv.org.

In The Last Decade

Duc Le

29 papers receiving 588 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Duc Le United States 15 485 291 147 125 57 30 672
Hideki Banno Japan 11 319 0.7× 403 1.4× 162 1.1× 127 1.0× 39 0.7× 37 579
Emre Yılmaz Netherlands 14 485 1.0× 358 1.2× 74 0.5× 93 0.7× 37 0.6× 58 677
Andreas Tsiartas United States 13 297 0.6× 280 1.0× 154 1.0× 84 0.7× 70 1.2× 35 632
Christophe Veaux France 13 753 1.6× 791 2.7× 105 0.7× 126 1.0× 68 1.2× 35 1.1k
Fasih Haider United Kingdom 9 214 0.4× 95 0.3× 123 0.8× 82 0.7× 53 0.9× 50 477
John-Paul Hosom United States 12 516 1.1× 251 0.9× 185 1.3× 156 1.2× 125 2.2× 26 771
Ryuichi Nisimura Japan 10 301 0.6× 282 1.0× 123 0.8× 92 0.7× 14 0.2× 37 501
Slim Ouni France 11 177 0.4× 203 0.7× 192 1.3× 46 0.4× 28 0.5× 51 370
Raymond Brueckner Germany 7 362 0.7× 426 1.5× 398 2.7× 88 0.7× 22 0.4× 13 710
Jeffrey Berry United States 12 151 0.3× 129 0.4× 199 1.4× 78 0.6× 59 1.0× 34 389

Countries citing papers authored by Duc Le

Since Specialization
Citations

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

Fields of papers citing papers by Duc Le

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Duc Le. 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 Duc Le. The network helps show where Duc Le may publish in the future.

Co-authorship network of co-authors of Duc Le

This figure shows the co-authorship network connecting the top 25 collaborators of Duc Le. A scholar is included among the top collaborators of Duc Le 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 Duc Le. Duc Le 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.
Moritz, Niko, Frank Seide, Duc Le, Jay Mahadeokar, & Christian Fuegen. (2023). An Investigation of Monotonic Transducers for Large-Scale Automatic Speech Recognition. 324–330. 5 indexed citations
2.
Tjandra, Andros, et al.. (2023). Learning ASR Pathways: A Sparse Multilingual ASR Model. 1–5. 4 indexed citations
3.
Bruguier, Antoine, Duc Le, Rohit Prabhavalkar, et al.. (2022). Neural-FST Class Language Model for End-to-End Speech Recognition. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 18. 6107–6111. 3 indexed citations
4.
Kim, Suyoun, Duc Le, Tarun Pal Singh, et al.. (2022). Evaluating User Perception of Speech Recognition System Quality with Semantic Distance Metric. Interspeech 2022. 5 indexed citations
5.
Xiao, Alex, Gil Keren, Duc Le, et al.. (2022). Scaling ASR Improves Zero and Few Shot Learning. Interspeech 2022. 5135–5139. 5 indexed citations
6.
Le, Duc, Mahaveer Jain, Gil Keren, et al.. (2021). Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow Fusion. 1772–1776. 44 indexed citations
7.
Le, Duc, Gil Keren, Julian Chan, et al.. (2021). Deep Shallow Fusion for RNN-T Personalization. 251–257. 42 indexed citations
8.
Shi, Yangyang, Chunyang Wu, Jay Mahadeokar, et al.. (2021). Dynamic Encoder Transducer: A Flexible Solution for Trading Off Accuracy for Latency. 2042–2046. 6 indexed citations
9.
Le, Duc, et al.. (2020). G2G: TTS-Driven Pronunciation Learning for Graphemic Hybrid ASR. 10 indexed citations
10.
Shi, Yangyang, Yongqiang Wang, Chunyang Wu, et al.. (2020). Weak-Attention Suppression for Transformer Based Speech Recognition. 4996–5000. 12 indexed citations
11.
Le, Duc, et al.. (2019). From Senones to Chenones: Tied Context-Dependent Graphemes for Hybrid Speech Recognition. 457–464. 33 indexed citations
12.
Perez, Matthew, Wenyu Jin, Duc Le, et al.. (2018). Classification of Huntington Disease Using Acoustic and Lexical Features. PubMed. 2018. 1898–1902. 29 indexed citations
13.
Le, Duc. (2017). Towards Automatic Speech-Language Assessment for Aphasia Rehabilitation. Deep Blue (University of Michigan). 3 indexed citations
14.
Le, Duc, et al.. (2017). Automatic Paraphasia Detection from Aphasic Speech: A Preliminary Study. 294–298. 19 indexed citations
15.
Le, Duc & Emily Mower Provost. (2016). Improving Automatic Recognition of Aphasic Speech with AphasiaBank. 2681–2685. 34 indexed citations
16.
Le, Duc, et al.. (2016). Automatic Assessment of Speech Intelligibility for Individuals With Aphasia. IEEE/ACM Transactions on Audio Speech and Language Processing. 24(11). 2187–2199. 45 indexed citations
17.
18.
Le, Duc, et al.. (2014). Automatic analysis of speech quality for aphasia treatment. 4853–4857. 20 indexed citations
19.
20.
Le, Duc & Emily Mower Provost. (2013). Emotion recognition from spontaneous speech using Hidden Markov models with deep belief networks. 216–221. 82 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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