@InProceedings{8553512,
  author = {A. E. Jaramillo and J. K. Nielsen and M. G. Christensen},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {On Optimal Filtering for Speech Decomposition},
  year = {2018},
  pages = {2325-2329},
  abstract = {Optimal linear filtering has been used extensively for speech enhancement. In this paper, we take a first step in trying to apply linear filtering to the decomposition of a noisy speech signal into its components. The problem of decomposing speech into its voiced and unvoiced components is considered as an estimation problem. Assuming a harmonic model for the voiced speech, we propose a Wiener filtering scheme which estimates both components separately in the presence of noise. It is shown under which conditions this optimal filtering formulation outperforms two state-of-the-art speech decomposition methods, which is also revealed by objective measures, spectrograms and informal listening tests.},
  keywords = {decomposition;estimation theory;harmonic analysis;speech enhancement;Wiener filters;informal listening testing;spectrograms;voiced speech harmonic model;noisy speech signal decomposition methods;Wiener filtering scheme;estimation problem;unvoiced components;voiced components;speech enhancement;optimal linear filtering;Harmonic analysis;Noise measurement;Speech processing;Covariance matrices;Spectrogram;Estimation;Europe;Speech decomposition;time-domain filtering;Wiener filter;voiced speech;unvoiced speech},
  doi = {10.23919/EUSIPCO.2018.8553512},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570437959.pdf},
}

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