HMM-BASED SPEECH SYNTHESIS ADAPTATION USING NOISY DATA:
ANALYSIS AND EVALUATION METHODS

Reima Karhila, Ulpu Remes and Mikko Kurimo
Department of Information and Computer Science, Aalto University School of Science, Finland

The paper submitted to ICASSP-13 investigated the effects of noise in HMM-based speech synthesis. The research was done by artificially corrupting clean speech with noise from NOISEX-92 database and using the noisy data to a clean average voice to target speakers.

Below you will find samples used in the work.
The listening test developed in this work can be found here.

Male speaker

Female speaker