Using instantaneous frequency and aperiodicity detection to estimate F0 for high-quality speech synthesis
This work addresses the need for precise F0 and aperiodicity analysis in speech synthesis applications, representing an incremental improvement over prior methods.
The paper tackles the problem of accurately estimating F0 and aperiodicity for high-quality speech synthesis by introducing a new framework with subsystems for instantaneous frequency estimation, F0 tracking, and refinement. The result is a preliminary implementation that outperforms existing F0 extractors by a factor of 10 in RMS F0 estimation error.
This paper introduces a general and flexible framework for F0 and aperiodicity (additive non periodic component) analysis, specifically intended for high-quality speech synthesis and modification applications. The proposed framework consists of three subsystems: instantaneous frequency estimator and initial aperiodicity detector, F0 trajectory tracker, and F0 refinement and aperiodicity extractor. A preliminary implementation of the proposed framework substantially outperformed (by a factor of 10 in terms of RMS F0 estimation error) existing F0 extractors in tracking ability of temporally varying F0 trajectories. The front end aperiodicity detector consists of a complex-valued wavelet analysis filter with a highly selective temporal and spectral envelope. This front end aperiodicity detector uses a new measure that quantifies the deviation from periodicity. The measure is less sensitive to slow FM and AM and closely correlates with the signal to noise ratio.