Evaluation of Excitation Feature Prediction in a Hybrid Approach to Electrolaryngeal Speech Enhancement

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 the hybrid approach to 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 the 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.