2014/01/17 by Sira González, Mike Brookes · 1 citation
Computer Science · Engineering · #Speech and Audio Processing #Music and Audio Processing #Advanced Adaptive Filtering Techniques
paper · doi:10.1109/taslp.2013.2295918
openalex publication_date 2014/01/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/26
We present PEFAC, a fundamental frequency estimation algorithm for speech that is able to identify voiced frames and estimate pitch reliably even at negative signal-to-noise ratios. The algorithm combines a normalization stage, to remove channel dependency and to attenuate strong noise components, with a harmonic summing filter applied in the log-frequency power spectral domain, the impulse response of which is chosen to sum the energy of the fundamental frequency harmonics while attenuating smoothly-varying noise components. Temporal continuity constraints are applied to the selected pitch candidates and a voiced speech probability is computed from the likelihood ratio of two classifiers, one for voiced speech and one for unvoiced speech/silence. We compare the performance of our algorithm with that of other widely used algorithms and demonstrate that it performs well in both high and low levels of additive noise.