Brian Strope
- Artificial Intelligence top 1%
- Natural Language Processing Techniques 15
- Topic Modeling 14
- Speech Recognition and Synthesis 11
- Speech and dialogue systems 6
- Signal Processing top 5%
- Speech and Audio Processing 13
- Music and Audio Processing 6
- Information Systems top 5%
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- Hearing Loss and Rehabilitation 8
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- Acoustic Wave Phenomena Research 5
- Journals
- The Journal of the Acoustical Society of America (3 papers)IEEE Transactions on Speech and Audio Processing (1 paper)North American Chapter of the Association for Computational Linguistics (1 paper)
- Partner nations
- United StatesSwitzerlandSouth Africa
In The Last Decade
Brian Strope
29 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 1.2k
- Signal Processing 211
- Computer Vision and Pattern Recognition 218
- Information Systems 186
- Health Informatics 10
Countries citing papers authored by Brian Strope
This map shows the geographic impact of Brian Strope'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 Brian Strope with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Strope more than expected).
Fields of papers citing papers by Brian Strope
This network shows the impact of papers produced by Brian Strope. 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 Brian Strope. The network helps show where Brian Strope may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Brian Strope, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 228 | |
| 2 | 2019 | 49 | |
| 3 | Universal Sentence Encoder for Englishbreakdown → | 2018 | 705 |
| 4 | 2018 | 54 | |
| 5 | 2018 | 86 | |
| 6 | Generating Long and Diverse Responses with Neural Conversation Models | 2017 | 33 |
| 7 | 2017 | 92 | |
| 8 | Contextual LSTM: A Step towards Hierarchical Language Modeling | 2016 | 4 |
| 9 | 2013 | 12 | |
| 10 | Large-scale discriminative language model reranking for voice-search | 2012 | 3 |
| 11 | 2012 | 11 | |
| 12 | 2012 | 8 | |
| 13 | 2011 | 11 | |
| 14 | 2011 | 7 | |
| 15 | 2009 | 6 | |
| 16 | 2002 | 0 | |
| 17 | 2002 | 2 | |
| 18 | 1998 | 1 | |
| 19 | 1997 | 80 | |
| 20 | 1997 | 9 |
About Brian Strope
Brian Strope is a scholar working on Signal Processing, Artificial Intelligence and Cognitive Neuroscience, having authored 30 papers that have together received 1.5k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Topic Modeling (14 papers), Speech and Audio Processing (13 papers), Speech Recognition and Synthesis (11 papers), Hearing Loss and Rehabilitation (8 papers), Speech and dialogue systems (6 papers), Music and Audio Processing (6 papers) and Acoustic Wave Phenomena Research (5 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Signal Processing (211 citations) and Computer Vision and Pattern Recognition (218 citations). Brian Strope has collaborated with scholars based in United States, Switzerland and South Africa. Frequent co-authors include Ray Kurzweil, Yinfei Yang, Daniel Cer, Steve Yuan, Noah Constant, Chris Tar, Sheng-yi Kong, Nan Hua, A. Alwan and Yun-Hsuan Sung. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Transactions on Speech and Audio Processing, North American Chapter of the Association for Computational Linguistics, arXiv (Cornell University) and Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing.
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.