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Reconstruction of Mandarin Electrolaryngeal Fricatives With Hybrid Noise Source

Authors :
Ke Xiao
Liang Wu
Mingxi Wan
Supin Wang
Source :
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 27:383-391
Publication Year :
2019
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2019.

Abstract

The Mandarin electrolaryngeal EL speech is suffering from severe fricative confusion due to improper EL source in EL speech production and abnormal physiological structure of vocal tract in the laryngectomized condition. To reduce the fricative confusions, this paper proposes a hybrid noise source by combining the typical natural fricative sources and compensation sources that consider the acoustic defects in the frequency domain caused by the truncated vocal tract and abnormal source location in EL speech production. All parameters of the model are fricative-specific and the parameters of the compensation sources are determined by analyzing the vocal tract transfer functions before and after the laryngectomy. All five Mandarin fricatives are produced by laryngectomized subjects with an experimental EL system loading the hybrid noise source and the wideband noise source. The acoustic and perceptual features of these reconstructed EL fricatives are analyzed and evaluated by comparing with the conventional EL fricatives and normal fricatives. The results indicate that the hybrid noise source successfully improves the acoustic properties of the EL fricatives by forming better spectral shapes, raising the frequencies of average energy concentration, and producing better spectral skewness and kurtosis. Finally, due to these improvements of acoustic properties, the hybrid noise sources achieve much larger intelligibility for EL fricatives than the wideband noise source and the conventional EL source. Thus, the hybrid noise source is an effective, feasible, and promising method of reducing the severe fricative confusions and improving the intelligibility of EL speech.

Details

ISSN :
23299304 and 23299290
Volume :
27
Database :
OpenAIRE
Journal :
IEEE/ACM Transactions on Audio, Speech, and Language Processing
Accession number :
edsair.doi...........ff06b4eb0db25af252383e203a15d948
Full Text :
https://doi.org/10.1109/taslp.2018.2880607