BLASER: A Text-Free Speech-to-Speech Translation Evaluation Metric (2023.acl-long)
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Mingda Chen, Paul-Ambroise Duquenne, Pierre Andrews, Justine Kao, Alexandre Mourachko, Holger Schwenk, Marta R. Costa-jussà
| Challenge: | End-to-End speech-to speech translation is generally evaluated with text-based metrics . this means generated speech has to be automatically transcribed, making the evaluation dependent on ASR systems. |
| Approach: | They propose a text-free evaluation metric for end-to-end speech-tospeech translation, named BLASER, to avoid the dependency on automatic speech recognition systems. |
| Outcome: | The proposed metric avoids the dependency on automatic speech recognition systems by encoding generated speech segments into a shared embedding space. |
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