2025/07/30 by Sotheara Leang, Leang, Sotheara, Éric Castelli +5
Engineering · #Audio and Speech Processing (eess.AS) #Computation and Language (cs.CL) #FOS: Computer and information sciences #FOS: Electrical engineering #Fault Detection and Control Systems #Industrial Vision Systems and Defect Detection #Signal Processing (eess.SP) #Sound (cs.SD) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2507.22964
openalex publication_date 2025/07/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The dynamic characteristics of speech signal provides temporal information and play an important role in enhancing Automatic Speech Recognition (ASR). In this work, we characterized the acoustic transitions in a ratio plane of Spectral Subband Centroid Frequencies (SSCFs) using polar parameters to capture the dynamic characteristics of the speech and minimize spectral variation. These dynamic parameters were combined with Mel-Frequency Cepstral Coefficients (MFCCs) in Vietnamese ASR to capture more detailed spectral information. The SSCF0 was used as a pseudo-feature for the fundamental frequency (F0) to describe the tonal information robustly. The findings showed that the proposed parameters significantly reduce word error rates and exhibit greater gender independence than the baseline MFCCs.