Mirco Ravanelli
- Signal Processing top 2%
- Artificial Intelligence top 5%
- Computational Mechanics
- Cognitive Neuroscience
- Computer Vision and Pattern Recognition
- Co-authors
- Maurizio OmologoYu TsaoCheng YuSzu‐Wei FuXugang LuPeter PlantingaFrançois GrondinPiergiorgio Svaizer
- Topics
- Speech Recognition and Synthesis (21 papers)Speech and Audio Processing (20 papers)Music and Audio Processing (20 papers)
- Partner nations
- CanadaItalyUnited States
In The Last Decade
Mirco Ravanelli
29 papers receiving 371 citations
Peers
Comparison fields: 5 of 43
- Signal Processing 303
- Artificial Intelligence 251
- Computational Mechanics 48
- Cognitive Neuroscience 45
- Computer Vision and Pattern Recognition 36
Countries citing papers authored by Mirco Ravanelli
This map shows the geographic impact of Mirco Ravanelli'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 Mirco Ravanelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mirco Ravanelli more than expected).
Fields of papers citing papers by Mirco Ravanelli
This network shows the impact of papers produced by Mirco Ravanelli. 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 Mirco Ravanelli. The network helps show where Mirco Ravanelli may publish in the future.
Co-authorship network of co-authors of Mirco Ravanelli
This figure shows the co-authorship network connecting the top 25 collaborators of Mirco Ravanelli. A scholar is included among the top collaborators of Mirco Ravanelli 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 Mirco Ravanelli. Mirco Ravanelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 28 | |
| 11 | 2 | |
| 12 | 18 | |
| 13 | 46 | |
| 14 | 118 | |
| 15 | 2 | |
| 16 | 3 | |
| 17 | Audio-concept features and hidden Markov models for multimedia event detection. | 2 |
| 18 | The DIRHA simulated corpus | 44 |
| 19 | 2 | |
| 20 | Impulse response estimation for robust speech recognition in a reverberant environment | 20 |
About Mirco Ravanelli
Mirco Ravanelli is a scholar working on Signal Processing, Artificial Intelligence and Music, having authored 31 papers that have together received 390 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (21 papers), Speech and Audio Processing (20 papers) and Music and Audio Processing (20 papers). The work is most often cited by research in Signal Processing (303 citations), Artificial Intelligence (251 citations) and Computational Mechanics (48 citations). Mirco Ravanelli has collaborated with scholars based in Canada, Italy and United States. Frequent co-authors include Maurizio Omologo, Yu Tsao, Cheng Yu, Szu‐Wei Fu, Xugang Lu, Peter Plantinga, François Grondin, Piergiorgio Svaizer, Jenthe Thienpondt and Nauman Dawalatabad. Their work appears in journals such as Neural Networks, Computers in Biology and Medicine 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.