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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Flight Booking Screen Recordings

Dataset Description: This dataset contains screen recordings of users navigating the Expedia platform (www.expedia.com) to simulate booking a flight from any origin to any destination. Each recording is 1–3 minutes long, saved in MP4 or AVI format, and includes brief narration with an emotional tone (e.g., excitement or curiosity). The recordings stop at the payment page, with no personal information (e.g., names, addresses, credit card details) shown. The dataset is designed for AI training purposes, including user interface analysis, emotional tone classification, and human-computer interaction studies.

The dataset supports training and evaluation of models in:

Video analysis for user interface navigation
Audio classification for emotional tone detection
Human-computer interaction studies
AI-driven usability testing and improvement

Intended Uses

✅ Direct Use

Training and benchmarking models for video-based user interface analysis
Emotional tone classification from narrated audio
Research in human-computer interaction and user experience
Developing AI tools for automated usability testing

❌ Out-of-Scope Use

Real-time or production-grade booking systems
Commercial use without proper CC BY 4.0 attribution
Use for purposes violating privacy or copyright laws

Considerations and Limitations

❗ The dataset is small (<1,000 samples) and may not capture all possible user interactions or emotional tones
💡 Emotional narration is subjective, and classification results may vary by model or listener
🔄 Future versions will aim to include recordings from diverse devices, browsers, and user demographics

License

CC BY 4.0 — You can use, modify, and share the dataset with appropriate credit.

Contact

For queries or collaborations related to datasets, contact at :
- anoushka@kgen.io
- abhishek.vadapalli@kgen.io

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Total file size:

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Models trained or fine-tuned on HumynLabs/flight-booking-screen-recording

andrew2009/axi0n

Text Classification • Updated Aug 3, 2025