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Datasets:
zant-os
/
zant-echo-golden

Modalities:
Audio
Formats:
soundfolder
Size:
< 1K
Libraries:
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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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license: cc0-1.0 task_categories: - audio-classification language: - en tags: - speaker-diarization - test-dataset size_categories: - n<1K

ZantOS Golden Test Set

Human-recorded meeting audio with ground truth speaker annotations for acceptance testing.

Dataset Details

  • Version: 1.0.0
  • Clips: 3 meetings (2-4 minutes each)
  • Speakers: 2-4 per clip
  • Format: 16kHz mono WAV
  • Annotation: RTTM format (Rich Transcription Time Marked)

Structure

v1.0.0/ ├── metadata.json # Dataset version info ├── audio/ │ ├── meeting_001.wav # 3 min, 2 speakers, clear audio │ ├── meeting_002.wav # 4 min, 3 speakers, some cross-talk │ └── meeting_003.wav # 2 min, 4 speakers, challenging └── reference/ ├── meeting_001.rttm # Ground truth annotations ├── meeting_002.rttm └── meeting_003.rttm

RTTM Format

Each line represents a speaker segment: SPEAKER meeting_001 1 0.00 5.32 speaker_0 SPEAKER meeting_001 1 5.32 12.15 speaker_1

Fields: type file channel start duration _ _ speaker_id _ _

Usage

Download via Python:

from datasets import load_dataset

dataset = load_dataset("zant-os/zant-echo-golden", split="v1.0.0")

Or clone directly:
git clone https://huggingface.co/datasets/zant-os/zant-echo-golden

Quality Targets

- DER (Diarization Error Rate): ≤18%
- Speaker detection accuracy: ≥95%
- Overlap handling: Graceful degradation

License

CC0 1.0 Universal (Public Domain)
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