In Other News: A Bi-style Text-to-speech Modelfor Synthesizing Newscaster Voice with Limited Data
Tablica 3: Objective metrics for analysis of prosody and segmental quality. High FCORR indicates better prosody. For all other metrics, lower value indicates better performance.
['[BOLD] System', '[BOLD] Segmental Quality  [BOLD] MSD (dB)', '[BOLD] Prosody  [BOLD] FRMSE (Hz)', '[BOLD] Prosody  [BOLD] FCORR', '[BOLD] Prosody  [BOLD] GPE (%)', '[BOLD] Prosody  [BOLD] FPE (cents)']
We observe that both of our newscaster-style models obtain consistently better scores on all metrics, than neutral NTTS and concatenative-based system. Furthermore, we also observe that conditioning the newscaster-style model with CWE helps improve the prosody of the synthesised utterances. There’s a slight loss in segmental quality when conditioning the model with CWE, but it appears to be imperceptible to human listeners.