摘要
In this paper, a new event detection pitch detector based on the dyadic wavelet transform was constrcted by selecting an optimal scale. The proposed pitch detector is accurate, robust to noise and computationally simple. Experiments show the superior performance of this event-based pitch detector in comparison with previous event-based pitch detector and classical pitch detectors that use the autocorrelation and the cepsmun methods to estimate the pitch period.
In this paper, a new event detection pitch detector based on the dyadic wavelet transform was constrcted by selecting an optimal scale. The proposed pitch detector is accurate, robust to noise and computationally simple. Experiments show the superior performance of this event-based pitch detector in comparison with previous event-based pitch detector and classical pitch detectors that use the autocorrelation and the cepsmun methods to estimate the pitch period.
基金
ProjectsupportedbytheNationalNaturalScienceFoundationofChina(GrantNo.10271074)
