DocumentCode
179191
Title
An evaluation of excitation feature prediction in a hybrid approach to electrolaryngeal speech enhancement
Author
Tanaka, Kiyoshi ; Toda, Takechi ; Neubig, Graham ; Sakti, Sakriani ; Nakamura, Shigenari
Author_Institution
Grad. Sch. of Inf. Sci., Nara Inst. of Sci. & Technol., Ikoma, Japan
fYear
2014
fDate
4-9 May 2014
Firstpage
4488
Lastpage
4492
Abstract
We implement removing micro-prosody with low-pass filtering and avoiding Unvoiced/Voiced (U/V) prediction as part of a hybrid approach to improve statistical excitation prediction in electrolaryngeal (EL) speech enhancement. An electrolarynx is a device that artificially generates excitation sounds to enable laryngectomees to produce EL speech. Although proficient laryngectomees can produce quite intelligible EL speech, it sounds very unnatural due to the mechanical excitation produced by the device. Moreover, the excitation sounds produced by the device often leak outside, adding noise to EL speech. To address these issues, in our previous work, we proposed a hybrid method using a noise reduction method for enhancing spectral parameters and voice conversion method for predicting excitation parameters. In this paper, we evaluate the effect of removing micro-prosody with low-pass filtering and avoiding U/V prediction in the hybrid enhancement process.
Keywords
low-pass filters; speech enhancement; EL speech enhancement; U/V; Unvoiced/Voiced prediction; electrolaryngeal; electrolaryngeal speech enhancement; excitation feature prediction; hybrid approach; hybrid enhancement process; low pass filtering; mechanical excitation; microprosody; noise reduction method; proficient laryngectomees; spectral parameters; statistical excitation prediction; voice conversion method; Degradation; Estimation; Speech; Speech enhancement; Training; Vectors; electrolaryngeal speech; hybrid approach; speaking aid; statistical excitation prediction; unvoiced/voiced information;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6854451
Filename
6854451
Link To Document