Wade Shen

7.5k total citations · 2 hit papers
49 papers, 5.0k citations indexed

About

Wade Shen is a scholar working on Artificial Intelligence, Signal Processing and Linguistics and Language. According to data from OpenAlex, Wade Shen has authored 49 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Artificial Intelligence, 19 papers in Signal Processing and 3 papers in Linguistics and Language. Recurrent topics in Wade Shen's work include Natural Language Processing Techniques (31 papers), Speech Recognition and Synthesis (30 papers) and Music and Audio Processing (15 papers). Wade Shen is often cited by papers focused on Natural Language Processing Techniques (31 papers), Speech Recognition and Synthesis (30 papers) and Music and Audio Processing (15 papers). Wade Shen collaborates with scholars based in United States, Germany and Czechia. Wade Shen's co-authors include Marcello Federico, Richard Zens, Nicola Bertoldi, Hieu Hoang, Ondřej Bojar, Philipp Koehn, Chris Dyer, Evan Herbst, Brooke Cowan and Alexandra Constantin and has published in prestigious journals such as The Journal of the Acoustical Society of America, IEEE Signal Processing Magazine and IEEE Transactions on Audio Speech and Language Processing.

In The Last Decade

Wade Shen

47 papers receiving 4.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Moses

2007 3.2k citations Philipp Koehn, Richard Zens et al. profile →
Moses: Open Source Toolkit for Statistical Machine Translation

2007 1.1k citations Philipp Koehn, Hieu Hoang et al. Edinburgh Research Explorer (University of Edinburgh) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wade Shen United States	15	4.9k	803	524	335	230	49	5.0k
Marcello Federico Italy	32	7.4k 1.5×	1.4k 1.7×	260 0.5×	489 1.5×	409 1.8×	182	7.6k
Hitoshi Isahara Japan	26	2.4k 0.5×	354 0.4×	160 0.3×	138 0.4×	281 1.2×	236	2.6k
Eiichiro Sumita Japan	32	3.8k 0.8×	940 1.2×	96 0.2×	203 0.6×	184 0.8×	333	4.0k
Lucia Specia United Kingdom	35	4.0k 0.8×	723 0.9×	93 0.2×	170 0.5×	355 1.5×	213	4.3k
Nicola Bertoldi Italy	18	5.2k 1.1×	886 1.1×	64 0.1×	380 1.1×	310 1.3×	67	5.3k
Christof Monz Netherlands	27	3.4k 0.7×	556 0.7×	82 0.2×	194 0.6×	416 1.8×	113	3.6k
Thorsten Brants Germany	21	2.3k 0.5×	197 0.2×	96 0.2×	150 0.4×	401 1.7×	38	2.6k
Nianwen Xue United States	32	4.0k 0.8×	451 0.6×	30 0.1×	424 1.3×	204 0.9×	108	4.1k
Grzegorz Kondrak Canada	25	1.5k 0.3×	206 0.3×	138 0.3×	68 0.2×	110 0.5×	92	1.7k
Anoop Sarkar Canada	22	1.8k 0.4×	333 0.4×	43 0.1×	151 0.5×	144 0.6×	96	2.1k

Countries citing papers authored by Wade Shen

Since Specialization

Citations

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

Fields of papers citing papers by Wade Shen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wade Shen

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Shen, Wade. (2018). DARPA's Data Driven Discovery of Models (D3M) and Software Defined Hardware (SDH) Programs. 1–1. 3 indexed citations

2.

Baydin, Atılım Güneş, Robert Zinkov, William T. Harvey, et al.. (2017). End-to-end Training of Differentiable Pipelines Across Machine Learning Frameworks. 5 indexed citations

3.

Williams, Jennifer, et al.. (2014). Finding Good Enough: A Task-Based Evaluation of Query Biased Summarization for Cross-Language Information Retrieval. 657–669. 3 indexed citations

4.

Ray, Jessica M., Brian J. Thompson, & Wade Shen. (2014). Comparing a High and Low-Level Deep Neural Network Implementation for Automatic Speech Recognition. 41–46. 7 indexed citations

5.

Chen, Nancy F., Wade Shen, & Joseph P. Campbell. (2012). Analyzing and interpreting automatically learned rules across dialects. 1307–1310. 1 indexed citations

6.

Chen, Nancy F., Wade Shen, & Joseph P. Campbell. (2010). A linguistically-informative approach to dialect recognition using dialect-discriminating context-dependent phonetic models. 5014–5017. 29 indexed citations

7.

Chen, Nancy F., Wade Shen, Joseph P. Campbell, & Reva Schwartz. (2009). Large-scale analysis of formant frequency estimation variability in conversational telephone speech. 2203–2206. 7 indexed citations

8.

Cieri, Christopher, et al.. (2008). Bridging the Gap between Linguists and Technology Developers: Large-Scale, Sociolinguistic Annotation for Dialect and Speaker Recognition.. Language Resources and Evaluation. 3 indexed citations

9.

Shen, Wade, Nancy F. Chen, & Douglas A. Reynolds. (2008). Dialect recognition using adapted phonetic models. 763–766. 15 indexed citations

10.

Bertoldi, Nicola, Richard Zens, Marcello Federico, & Wade Shen. (2008). Efficient Speech Translation Through Confusion Network Decoding. IEEE Transactions on Audio Speech and Language Processing. 16(8). 1696–1705. 17 indexed citations

11.

Shen, Wade, Joseph P. Olive, & Douglas L. Jones. (2008). Two protocols comparing human and machine phonetic recognition performance in conversational speech. 1630–1633. 8 indexed citations

12.

Koehn, Philipp, Hieu Hoang, Alexandra Birch, et al.. (2007). Moses: Open Source Toolkit for Statistical Machine Translation. Edinburgh Research Explorer (University of Edinburgh). 1105 indexed citations breakdown →

13.

Campbell, William M., Douglas Sturim, Wade Shen, D.A. Reynolds, & Jiří Navrátil. (2007). The MIT-LL/IBM 2006 Speaker Recognition System: High-Performance Reduced-Complexity Recognition. IV–217. 17 indexed citations

14.

Koehn, Philipp, Richard Zens, Chris Dyer, et al.. (2007). Moses. 177–177. 3165 indexed citations breakdown →

15.

Shen, Wade, Richard Zens, Nicola Bertoldi, & Marcello Federico. (2006). The JHU Workshop 2006 IWSLT System. RWTH Publications (RWTH Aachen). 59–63. 11 indexed citations

16.

Shen, Wade, et al.. (2006). An efficient graph search decoder for phrase-based statistical machine translation.. IWSLT. 197–204. 2 indexed citations

17.

Campbell, William M., Terry Gleason, Jiří Navrátil, et al.. (2006). Advanced Language Recognition using Cepstra and Phonotactics: MITLL System Performance on the NIST 2005 Language Recognition Evaluation. 1–8. 30 indexed citations

18.

Koehn, Philipp, Marcello Federico, Wade Shen, et al.. (2006). Open Source Toolkit for Statistical Machine Translation: Factored Translation Models and Lattice Decoding. 6 indexed citations

19.

Shen, Wade, et al.. (2005). The MITLL/AFRL MT System. IWSLT. 99–103. 3 indexed citations

20.

Clifford, Ray, et al.. (2004). The Effect of Text Difficulty on Machine Translation Performance -- A Pilot Study with ILR-Rated Texts in Spanish, Farsi, Arabic, Russian and Korean. Language Resources and Evaluation. 6 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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