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The JWT signature verification failed. Check the signing key and the algorithm.
Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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WMT Human + TTS Audio

WMT human evaluation data (zouharvi/wmt-human-all) extended with TTS-synthesised source audio, covering 49 language pairs. Used as training data for SpeechCOMET.

Part of the SpeechCOMET model family | Paper: Why We Need Speech to Evaluate Speech Translation (Züfle et al., 2026) | Code: github.com/MaikeZuefle/speechCOMET

Dataset

Each row contains a source sentence, a machine translation hypothesis, a human quality score, and TTS-synthesised source audio.

Column Type Description
src_text string Source sentence
tgt_text string MT hypothesis
score float Human quality score
audio Audio (24 kHz) TTS-synthesised source speech

Splits: train, validation

TTS synthesis

Audio is synthesised from the source text using:

  • Kokoro for English, Japanese, Chinese, Spanish, French, Hindi, Italian, and Portuguese (voice randomly selected per source sentence for diversity)
  • MMS-TTS (facebook/mms-tts-{lang}) as fallback for all other languages

Synthesis can be reproduced using the data preparation scripts.

Citation

@misc{züfle2026needspeechevaluatespeech,
      title={Why We Need Speech to Evaluate Speech Translation},
      author={Maike Züfle and Danni Liu and Vilém Zouhar and Jan Niehues},
      year={2026},
      eprint={2605.28227},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2605.28227},
}
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