One-to-Many Multilingual End-to-End Speech Translation
Table 3: Results for multilingual direct SLT systems with 6 and 8 target languages.
['[EMPTY]', 'De', 'Nl', 'Es', 'Fr', 'It', 'Pt', 'Ro', 'Ru']
Number of languages. When training a system with all the 6 target languages (De, Nl, Es, Fr, It, Pt) When adding ASR data to the 6 languages, we observe improvements in most languages, and the new system is worse than the baseline only for Spanish and French, although the gap for French has been reduced to −0.9. However, using all the 8 target languages leads to worse results and adding ASR data contributes to worsen the performance in this case. We think that the reason is related to the relatively low number of parameters of our models (∼33 millions), which reduce their capability to learn and discriminate between a larger number of languages.