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Effective combination of pretrained models - KIT@IWSLT2022
Pretrained models in acoustic and textual modalities can potentially improve speech translation for both Cascade and End-to-end approaches.
KIT’s IWSLT 2021 Offline Speech Translation System
We describe a system in both cascaded condition and end-to-end condition.
Multilingual Speech Translation KIT @ IWSLT2021
This paper contains the description for the submission of Karlsruhe Institute of Technology (KIT) for the multilingual TEDx translation task in the IWSLT 2021 evaluation campaign.
Improving Pronunciation and Accent Conversion through Knowledge Distillation And Synthetic Ground-Truth from Native TTS
Hence, we developed a new AC approach that not only focuses on accent conversion but also improves pronunciation of non-native accented speaker.
Accent conversion using discrete units with parallel data synthesized from controllable accented TTS
The goal of accent conversion (AC) is to convert speech accents while preserving content and speaker identity.
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