On the Parameter Estimation of Sinusoidal Models for Speech and Audio Signals

Research paper compares three sinusoidal models for speech and audio signal processing: standard Sinusoidal Model (SM), Exponentially Damped Sinusoidal Model (EDSM), and extended adaptive Quasi-Harmonic Model (eaQHM). The study finds eaQHM performs better for medium-to-large window analysis while EDSM excels with smaller analysis windows, suggesting future research should combine both approaches.

• →Three sinusoidal models were evaluated for speech and audio parameter estimation performance across different window sizes.
• →eaQHM outperforms EDSM in medium-to-large window size analysis scenarios.
• →EDSM provides higher reconstruction accuracy for smaller analysis window sizes.
• →Testing was conducted on both synthetic signals and real highly non-stationary signals like singing voices and guitar solos.
• →Future research should merge eaQHM's adaptivity with EDSM's parameter estimation robustness for improved audio signal processing.