Matteo Gerosa
- Signal Processing top 2%
- Speech and Audio Processing 8
- Music and Audio Processing 4
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- Phonetics and Phonology Research 8
- Artificial Intelligence top 2%
- Speech Recognition and Synthesis 18
- Speech and dialogue systems 9
- Natural Language Processing Techniques 7
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- Reading and Literacy Development 3
- Language and Linguistics top 5%
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- E-Government and Public Services 3
- Co-authors
- Diego GiulianiFabio BrugnaraShrikanth NarayananOrnella MichAmbra NeriAlexandros PotamianosStefan SteidlAnton Batliner
- Journals
- Speech Communication (2 papers)Computer Assisted Language Learning (1 paper)Computer Speech & Language (1 paper)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Matteo Gerosa
26 papers receiving 600 citations
Peers
Comparison fields: 5 of 52
- Signal Processing 314
- Experimental and Cognitive Psychology 237
- Artificial Intelligence 572
- Developmental and Educational Psychology 104
- Language and Linguistics 74
Countries citing papers authored by Matteo Gerosa
This map shows the geographic impact of Matteo Gerosa'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 Matteo Gerosa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Gerosa more than expected).
Fields of papers citing papers by Matteo Gerosa
This network shows the impact of papers produced by Matteo Gerosa. 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 Matteo Gerosa. The network helps show where Matteo Gerosa may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Matteo Gerosa, 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 | 2024 | 1 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 2 | |
| 4 | 2010 | 1 | |
| 5 | 2009 | 2 | |
| 6 | 2009 | 16 | |
| 7 | 2009 | 4 | |
| 8 | 2009 | 105 | |
| 9 | 2008 | 6 | |
| 10 | A generative model for scoring children 2 s reading comprehension. | 2008 | 2 |
| 11 | 2008 | 4 | |
| 12 | Detecting Problems in Spoken Child-Computer Interaction | 2008 | 5 |
| 13 | 2007 | 34 | |
| 14 | 2007 | 17 | |
| 15 | 2006 | 34 | |
| 16 | 2006 | 7 | |
| 17 | 2005 | 123 | |
| 18 | 2004 | 11 | |
| 19 | 2004 | 6 | |
| 20 | 2003 | 65 |
About Matteo Gerosa
Matteo Gerosa is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 26 papers that have together received 716 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (18 papers), Speech and dialogue systems (9 papers), Speech and Audio Processing (8 papers), Phonetics and Phonology Research (8 papers), Natural Language Processing Techniques (7 papers), Music and Audio Processing (4 papers), E-Government and Public Services (3 papers) and Reading and Literacy Development (3 papers). The work is most often cited by research in Signal Processing (314 citations), Experimental and Cognitive Psychology (237 citations) and Artificial Intelligence (572 citations). Matteo Gerosa has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Diego Giuliani, Fabio Brugnara, Shrikanth Narayanan, Ornella Mich, Ambra Neri, Alexandros Potamianos, Stefan Steidl, Anton Batliner, Martin Russell and Christian Hacker. Their work appears in journals such as Speech Communication, Computer Assisted Language Learning, Computer Speech & Language, Digital Government Research and Practice and Zenodo (CERN European Organization for Nuclear Research).
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.