Wolfgang Macherey

8.7k total citations
23 papers, 1.1k citations indexed

About

Wolfgang Macherey is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Wolfgang Macherey has authored 23 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 8 papers in Signal Processing and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Wolfgang Macherey's work include Natural Language Processing Techniques (18 papers), Topic Modeling (12 papers) and Speech Recognition and Synthesis (12 papers). Wolfgang Macherey is often cited by papers focused on Natural Language Processing Techniques (18 papers), Topic Modeling (12 papers) and Speech Recognition and Synthesis (12 papers). Wolfgang Macherey collaborates with scholars based in Germany and United States. Wolfgang Macherey's co-authors include Franz Josef Och, Hermann Ney, Jakob Uszkoreit, Ralf Schlüter, Shankar Kumar, David Grangier, Markus Freitag, Viresh Ratnakar, George Foster and Qijun Tan and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Speech Communication and Transactions of the Association for Computational Linguistics.

In The Last Decade

Wolfgang Macherey

23 papers receiving 919 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wolfgang Macherey Germany 15 986 176 175 39 38 23 1.1k
Fumiaki Sugaya Japan 10 359 0.4× 98 0.6× 68 0.4× 66 1.7× 17 0.4× 36 511
Juan Miguel Vilar Spain 11 371 0.4× 85 0.5× 48 0.3× 17 0.4× 13 0.3× 30 449
Yoshihiko Gotoh United Kingdom 13 459 0.5× 157 0.9× 99 0.6× 51 1.3× 10 0.3× 49 584
Katsuhito Sudoh Japan 15 791 0.8× 157 0.9× 19 0.1× 37 0.9× 41 1.1× 96 829
Karl Stratos United States 16 697 0.7× 496 2.8× 34 0.2× 36 0.9× 21 0.6× 38 947
Naushad UzZaman United States 11 527 0.5× 63 0.4× 68 0.4× 31 0.8× 75 2.0× 22 564
Roldano Cattoni Italy 13 585 0.6× 156 0.9× 34 0.2× 31 0.8× 16 0.4× 39 676
Christian Federmann Germany 15 1.3k 1.3× 248 1.4× 26 0.1× 113 2.9× 81 2.1× 44 1.4k
Boxing Chen China 18 902 0.9× 242 1.4× 20 0.1× 97 2.5× 41 1.1× 88 962
Rabih Zbib United States 8 508 0.5× 87 0.5× 19 0.1× 36 0.9× 26 0.7× 18 545

Countries citing papers authored by Wolfgang Macherey

Since Specialization
Citations

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

Fields of papers citing papers by Wolfgang Macherey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wolfgang Macherey

This figure shows the co-authorship network connecting the top 25 collaborators of Wolfgang Macherey. A scholar is included among the top collaborators of Wolfgang Macherey 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 Wolfgang Macherey. Wolfgang Macherey 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.
Cheng, Yong, Ankur Bapna, Orhan Fırat, et al.. (2022). Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 4092–4102. 7 indexed citations
2.
Freitag, Markus, George Foster, David Grangier, et al.. (2021). Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation. Transactions of the Association for Computational Linguistics. 9. 1460–1474. 145 indexed citations
3.
Ye, Jia, Melvin Johnson, Wolfgang Macherey, et al.. (2019). Leveraging Weakly Supervised Data to Improve End-to-end Speech-to-text Translation. 7180–7184. 81 indexed citations
4.
Ye, Jia, Ron J. Weiss, Fadi Biadsy, et al.. (2019). Direct Speech-to-Speech Translation with a Sequence-to-Sequence Model. 1123–1127. 85 indexed citations
5.
Wang, Wei, Klaus Macherey, Wolfgang Macherey, Franz Josef Och, & Peng Xu. (2012). Improved Domain Adaptation for Statistical Machine Translation. Conference of the Association for Machine Translation in the Americas. 15 indexed citations
6.
Allauzen, Cyril, Shankar Kumar, Wolfgang Macherey, Mehryar Mohri, & Michael Riley. (2010). Expected Sequence Similarity Maximization. North American Chapter of the Association for Computational Linguistics. 957–965. 3 indexed citations
7.
Kumar, Shankar, Wolfgang Macherey, Chris Dyer, & Franz Josef Och. (2009). Efficient Minimum Error Rate Training and Minimum Bayes-Risk decoding for translation hypergraphs and lattices. 1. 163–163. 60 indexed citations
8.
Kumar, Shankar, et al.. (2008). Lattice Minimum Bayes-Risk decoding for statistical machine translation. 620–620. 88 indexed citations
9.
Macherey, Wolfgang, et al.. (2008). Lattice-based minimum error rate training for statistical machine translation. 725–725. 248 indexed citations
10.
Kumar, Shankar, Franz Josef Och, & Wolfgang Macherey. (2007). Improving Word Alignment with Bridge Languages. Empirical Methods in Natural Language Processing. 42–50. 36 indexed citations
11.
Macherey, Wolfgang & Franz Josef Och. (2007). An Empirical Study on Computing Consensus Translations from Multiple Machine Translation Systems. Empirical Methods in Natural Language Processing. 986–995. 38 indexed citations
12.
13.
Keysers, Daniel, et al.. (2004). Adaptation in statistical pattern recognition using tangent vectors. IEEE Transactions on Pattern Analysis and Machine Intelligence. 26(2). 269–274. 34 indexed citations
14.
15.
Macherey, Wolfgang, et al.. (2003). Probabilistic Aspects in Spoken Document Retrieval. EURASIP Journal on Advances in Signal Processing. 2003(2). 2 indexed citations
16.
Macherey, Wolfgang, et al.. (2002). Probabilistic retrieval based on document representations. 1481–1484. 1 indexed citations
17.
Macherey, Wolfgang & Hermann Ney. (2002). Towards automatic corpus preparation for a German broadcast news transcription system. IEEE International Conference on Acoustics Speech and Signal Processing. 1. I–733. 6 indexed citations
18.
Macherey, Wolfgang, et al.. (2001). Improving automatic speech recognition using tangent distance. 1825–1828. 4 indexed citations
19.
Schlüter, Ralf, Wolfgang Macherey, Boris Müller, & Hermann Ney. (2001). Comparison of discriminative training criteria and optimization methods for speech recognition. Speech Communication. 34(3). 287–310. 74 indexed citations
20.
Schlüter, Ralf, Wolfgang Macherey, Stephan Kanthak, Hermann Ney, & L. Welling. (1997). Comparison of optimization methods for discriminative training criteria. 15–18. 18 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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