Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  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.
['Hideki Kawahara', 'Yannis Agiomyrgiannakis', 'Heiga Zen']
I am writing a research paper on a idea Using instantaneous frequency and aperiodicity detection to estimate F0 for high-quality speech synthesis
[{"from": "human", "value": "I am writing a research paper on a idea Using instantaneous frequency and aperiodicity detection to estimate F0 for high-quality speech synthesis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  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."}]