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result = evaluator.evaluate(
    eval_templates="audio_quality",
    inputs={
        "input_audio": "https://datasets-server.huggingface.co/assets/EarthSpeciesProject/NatureLM-audio-training/--/e98500754629b63dd8d2400c1a20798337da92f5/--/NatureLM-audio-training/train/0/audio/audio.wav"
    },
    model_name="turing_flash"
)

print(result.eval_results[0].output)
print(result.eval_results[0].reason)
Input
Required InputTypeDescription
input_audiostringThe file path or URL to the audio file to be evaluated
Output
FieldDescription
ResultReturns a numeric score where higher score indicates better audio quality
ReasonProvides a detailed explanation of the audio quality assessment

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What to do If you get Undesired Results

If the audio quality score is lower than expected:
  • Check for background noise or interference in the recording
  • Verify the recording environment is appropriate (e.g., proper acoustic treatment)
  • Ensure the microphone or recording device is of sufficient quality
  • Consider using noise reduction techniques in post-processing
  • Check for issues like clipping, distortion, or compression artifacts
  • Verify the audio file format and bitrate are appropriate for the intended use
  • Re-record in a more controlled environment if possible

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Comparing Audio Quality with Similar Evals

  • Audio Transcription: While Audio Quality evaluates the perceptual quality of the audio itself, Audio Transcription assesses the accuracy of converting speech in the audio to text.
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