Ricard Marxer
Biographic Data
| ID | 2788052 |
|---|---|
| NAME | Ricard Marxer |
| GIVEN NAMES | Ricard |
| FAMILY NAME | Marxer |
| SIGNATURE | MARXER R |
| AFFILIATIONS | Universitat Pompeu Fabra |
| ORCID | 0000-0001-5099-5059 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Applying machine learning to primate bioacoustics
This paper provides a comprehensive review of the use of computational bioacoustics as well as signal and speech processing techniques in the analysis of primate vocal communication. We explore the potential implications of machine learning and deep learning methods, from the use of simple supervised algorithms to more recent self‐supervised models, for processing and analyzing large data sets obtained within the emergence of passive acoustic mon…
Evaluation and combination of pitch estimation methods for melody extraction in symphonic classical music
The extraction of pitch information is arguably one of the most important tasks in automatic music description systems. However, previous research and evaluation datasets dealing with pitch estimation focused on relatively limited kinds of musical data. This work aims to broaden this scope by addressing symphonic western classical music recordings, focusing on pitch estimation for melody extraction. This material is characterized by a high number…
No prominent works on this page.
Evaluation and combination of pitch estimation methods for melody extraction in symphonic classical music
The extraction of pitch information is arguably one of the most important tasks in automatic music description systems. However, previous research and evaluation datasets dealing with pitch estimation focused on relatively limited kinds of musical data. This work aims to broaden this scope by addressing symphonic western classical music recordings, focusing on pitch estimation for melody extraction. This material is characterized by a high number…
Applying machine learning to primate bioacoustics
This paper provides a comprehensive review of the use of computational bioacoustics as well as signal and speech processing techniques in the analysis of primate vocal communication. We explore the potential implications of machine learning and deep learning methods, from the use of simple supervised algorithms to more recent self‐supervised models, for processing and analyzing large data sets obtained within the emergence of passive acoustic mon…
Artificial Intelligence (2 works) · Computer Science (2 works) · Music and Audio Processing (2 works) · Animal Vocal Communication and Behavior (1 work) · Annotation (1 work) · Art (1 work) · Artificial neural network (1 work) · Bioacoustics (1 work) · Biology (1 work) · Classical music (1 work)