JOURNAL ARTICLE

Improved method for epoch estimation in telephonic speech signals using zero frequency filtering

Abstract

Epochs are the locations correspond to glottal closure instants for voiced speech segments and onset of bursts or frication in unvoiced segments. In the recent years, the zero frequency filtering (ZFF) based epoch estimation has received a growing attention for clean or studio speech signals. The ZFF based epoch estimation exploits the impulse like excitation characteristics at the zero frequency (DC) region in speech. As the lower frequency regions in telephonic speech are significantly attenuated, ZFF approach gives degraded epoch estimation performance. Therefore, the objective of the present work is to propose refinements to the existing ZFF based epoch estimation algorithm for improved epoch estimation in telephonic speech. The strength of the impulses at the zero frequency region are enhanced by computing the Hilbert envelope (HE) of the speech which in turn improve the epoch estimation performance. The resonators located at the approximate F0 locations of the short term blocks of conventional zero frequency filtered signal, are also found to improve the epoch estimation performance in telephonic speech. The performance of the refined ZFF method is evaluated on 3 speaker voices (JMK, SLT and BDL) of CMU Arctic database having simultaneous speech and EGG recordings. The telephonic version of CMU Arctic database is simulated using tools provided by the international telecommunication union (ITU).

Keywords:
Computer science Speech recognition Zero (linguistics) Epoch (astronomy) Computer vision

Metrics

7
Cited By
1.09
FWCI (Field Weighted Citation Impact)
20
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Music and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
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