Improving Pitch Tracking Performance in Hard Noise Conditions by a Preprocessing Based on Mathematical Morphology
In this paper we show how a nonlinear preprocessing of speech signal -with high noise- based on morphological filters improves the performance of robust algorithms for pitch tracking (RAPT). This result happens for a very simple morphological filter. More sophisticated ones could even improve such r...
| Autores: | , , |
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| Tipo de documento: | capítulo de livro |
| Data de publicação: | 2009 |
| País: | España |
| Recursos: | UVic-UCC |
| Repositório: | RiUVic. Repositori institucional de la UVic-UCC |
| OAI Identifier: | oai:dspace.uvic.cat:10854/3004 |
| Acesso em linha: | http://hdl.handle.net/10854/3004 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Tractament del senyal |
| Resumo: | In this paper we show how a nonlinear preprocessing of speech signal -with high noise- based on morphological filters improves the performance of robust algorithms for pitch tracking (RAPT). This result happens for a very simple morphological filter. More sophisticated ones could even improve such results. Mathematical morphology is widely used in image processing and has a great amount of applications. Almost all its formulations derived in the two-dimensional framework are easily reformulated to be adapted to one-dimensional context |
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