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Automatically deriving categories for translation
Abstract
An accurate fundamental frequency (F0) estimation method for non-stationary, speech-like sounds is proposed based on the dif-ferential properties of the instantaneous frequencies of two sets of filter outputs. A specific type of fixed points of mapping from the filter center frequency to the output instantaneous frequency provides frequencies of the constituent sinusoidal components of the input signal. When the filter is made from an isometric Gabor function convoluted with a cardinal B-spline basis func-tion, the differential properties at the fixed points provide prac-tical estimates of the carrier-to-noise ratio of the corresponding components. These estimates are used to select the fundamental component and to integrate the F0 information distributed among the other harmonic components. 1.
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Citations
Cited by
YIN, a fundamental frequency estimator for speech and music
de Cheveigné, A., & Kawahara, H. (2002) · The Journal of the Acoustical Society of America · doi:10.1121/1.1458024 · Cited by 1,920
Belin, P., Fillion-Bilodeau, S., & Gosselin, F. (2008) · Behavior Research Methods · doi:10.3758/brm.40.2.531 · Cited by 473
Metadata
- Authors
- Barrachina, S., & Vilar, J. M.
- Venue
- 6th European Conference on Speech Communication and Technology
- Publisher
- ISCA
- Published
- 1999-09-05
- Pages
- 2415-2418
- OpenAlex
- W2141684970
- Cited by
- 178
- References
- 0
- FWCI
- 6.93
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Barrachina, S., & Vilar, J. M. (1999). Automatically deriving categories for translation. 6th European Conference on Speech Communication and Technology. https://doi.org/10.21437/eurospeech.1999-613
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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