Abstract

This work proposes a modified zero frequency filtering (ZFF) method for epoch extraction from emotional speech. Epochs refers the instants of maximum excitation of the vocal tract. In the conventional ZFF method, the epochs are estimated by trend removing the output of the zero frequency resonator (ZFR) using the window length equal to the average pitch period of the utterance. Use of this fixed window length for the epoch estimation causes spurious or missed estimation from the speech signals having rapid pitch variations like in emotional speech. This work therefore proposes a refined ZFF method for epoch estimation by trend removing the output of ZFR using the variable windows obtained by finding the average pitch periods for every fixed blocks of speech and low pass filtering the resulting trend removed signal segments using the estimated pitch as the cutoff frequency. The epoch estimation performance is evaluated for five different emotions in the German emotional speech corpus having simultaneous electro-glotto graph (EGG) recordings. The improved epoch estimation performance indicates the robustness of the proposed method against rapid pitch variations in emotional speech signals. The effectiveness of the proposed method is also confirmed by the improved epoch estimation performance on the Hindi emotional speech database.

Keywords:
Speech recognition Computer science Pitch detection algorithm Robustness (evolution) Vocal tract Speech processing

Metrics

26
Cited By
1.89
FWCI (Field Weighted Citation Impact)
16
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

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

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