Denoising applied to sound event detection using weighting non-negative matrix factorization
Some sound events (screams, gunshots ...) are often associated with situations of danger and violence. Nevertheless, the noise interference that appears with them decreases the detection performance to a great extent. Most existing methods that employ a trained noise classifier have the problem that...
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| Format: | master thesis |
| Publication Date: | 2021 |
| Country: | España |
| Institution: | Universidad de Jaén (UJA) |
| Repository: | CREA. Colección de recursos educativos abiertos |
| OAI Identifier: | oai:crea.ujaen.es:10953.1/13604 |
| Online Access: | https://hdl.handle.net/10953.1/13604 |
| Access Level: | Open access |
| Keyword: | 3325 Tecnología de las telecomunicaciones Telecommunications Technology |
| Summary: | Some sound events (screams, gunshots ...) are often associated with situations of danger and violence. Nevertheless, the noise interference that appears with them decreases the detection performance to a great extent. Most existing methods that employ a trained noise classifier have the problem that they cannot provide an optimal result when such noise does not resemble the trained noise or is highly variable in time. Therefore, the task of acoustic noise reduction in this acoustic scenario remains a great challenge for sound event detec-tion. For this Master Thesis, we propose the design and development of a system imple-mented in MATLAB capable of reducing noise for the detection of sound events using a Weighted Non-Negative Matrix factorization (WNMF) approach. |
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