Patrick Littell

1.1k citations
29 papers · 467 · h-index 9

Impact in

    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech Recognition and Synthesis
    • Speech and dialogue systems
    • Text Readability and Simplification
    • Linguistic Variation and Morphology

Papers in

Patrick Littell

27 papers receiving 380 citations

Peers

Patrick Littell
Comparison fields: 5 of 39
  • Artificial Intelligence 381
  • Linguistics and Language 47
  • Signal Processing 64
  • Experimental and Cognitive Psychology 54
  • Anthropology 39
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Countries citing papers authored by Patrick Littell

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Littell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Patrick Littell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Patrick Littell Line = papers co-authored together Patrick Littell links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017101
2 202064
3
Indigenous language technologies in Canada: Assessment, challenges, and successes
201862
4
PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors
201654
5 201852
6 201822
7
The Nunavut Hansard Inuktitut-English Parallel Corpus 3.0 with Preliminary Machine Translation Results.
202020
8
The Role of Context in Neural Morphological Disambiguation.
201612
9 201910
10
Named Entity Recognition for Linguistic Rapid Response in Low-Resource Languages: Sorani Kurdish and Tajik
20168
11 20177
12 20227
13 20186
14 20176
15 20165
16 20205
17 20144
18 20203
19
Finite-state morphology for Kwak’wala: A phonological approach
20183
20 20173

About Patrick Littell

Patrick Littell is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Language and Linguistics, Experimental and Cognitive Psychology and Linguistics and Language, having authored 29 papers that have together received 467 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Topic Modeling (20 papers), Speech Recognition and Synthesis (5 papers), Multimodal Machine Learning Applications (5 papers), Text Readability and Simplification (4 papers), Phonetics and Phonology Research (3 papers), Lexicography and Language Studies (2 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Artificial Intelligence (381 citations), Linguistics and Language (47 citations), Signal Processing (64 citations), Experimental and Cognitive Psychology (54 citations) and Anthropology (39 citations). Patrick Littell has collaborated with scholars based in United States, Canada and Japan. Frequent co-authors include David R. Mortensen, Lori Levin, Siddharth Dalmia, Chris Dyer, Kartik Goyal, Roland Kühn, Chi-kiu Lo, Marie-Odile Junker, Antti Arppe and Christopher Cox. Their work appears in journals such as Language Resources and Evaluation, Computer Speech & Language, Machine Translation, Lecture notes in computer science and International Conference on Computational Linguistics.

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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