Noah Coccaro
- Artificial Intelligence top 1%
- Experimental and Cognitive Psychology top 10%
- Signal Processing top 5%
- Language and Linguistics top 5%
- Information Systems top 10%
- Co-authors
- Daniel JurafskyRachel W. MartinRebecca BatesMarie MeteerCarol Van Ess-DykemaAndreas StolckeElizabeth ShribergKlaus Ries
- Topics
- Natural Language Processing Techniques (10 papers)Topic Modeling (7 papers)Speech and dialogue systems (6 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Noah Coccaro
14 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Artificial Intelligence 1.1k
- Experimental and Cognitive Psychology 145
- Signal Processing 135
- Language and Linguistics 105
- Information Systems 73
Countries citing papers authored by Noah Coccaro
This map shows the geographic impact of Noah Coccaro'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 Noah Coccaro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noah Coccaro more than expected).
Fields of papers citing papers by Noah Coccaro
This network shows the impact of papers produced by Noah Coccaro. 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 Noah Coccaro. The network helps show where Noah Coccaro may publish in the future.
Co-authorship network of co-authors of Noah Coccaro
This figure shows the co-authorship network connecting the top 25 collaborators of Noah Coccaro. A scholar is included among the top collaborators of Noah Coccaro 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 Noah Coccaro. Noah Coccaro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Text Normalization Infrastructure that Scales to Hundreds of Language Varieties | 7 |
| 2 | 76 | |
| 3 | 33 | |
| 4 | Latent semantic analysis as a tool to improve automatic speech recognition performance | 4 |
| 5 | 29 | |
| 6 | 66 | |
| 7 | 58 | |
| 8 | Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speechbreakdown → | 680 |
| 9 | 51 | |
| 10 | Dialog act modelling for conversational speech | 44 |
| 11 | 197 | |
| 12 | 1 | |
| 13 | Towards Spontaneous Speech Translation | 10 |
| 14 | 33 |
About Noah Coccaro
Noah Coccaro is a scholar working on Artificial Intelligence, Language and Linguistics and Signal Processing, having authored 14 papers that have together received 1.3k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (10 papers), Topic Modeling (7 papers) and Speech and dialogue systems (6 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Signal Processing (135 citations) and Experimental and Cognitive Psychology (145 citations). Noah Coccaro has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Daniel Jurafsky, Rachel W. Martin, Rebecca Bates, Marie Meteer, Carol Van Ess-Dykema, Andreas Stolcke, Elizabeth Shriberg, Klaus Ries, Paul Taylor and Paul Taylor. Their work appears in journals such as Computational Linguistics, Language and Speech and Language Resources and Evaluation.
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.