End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning
Table 2: Mean Opinion Score (MOS) ratings with 95% confidence intervals for naturalness.
['[BOLD] Method', '[BOLD] MOS score 25 minutes', '[BOLD] MOS score 15 minutes']
all of them outperform ”Scratch”. When training data is reduced to 15 minutes, ”Separate” degrades obviously, which is consistent with the discovery of previous objective tests. The results show that given a few but still sufficient paired data (25 min) on the target language, three transfer learning approaches can benefit from pretraining and generate intelligible speech. When paired data becomes fewer (15 min), our proposed approach ”Learned” is comparable to ”Unified” and gives promising results without using background linguistic expertise.