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Add compression_ratio_hallucination_threshold
Add compression_ratio_hallucination_threshold to Discard High Compression Ratio Segments in transcribe() https://github.com/openai/whisper/discussions/2420
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@ -42,11 +42,11 @@ def transcribe(
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verbose: Optional[bool] = None,
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temperature: Union[float, Tuple[float, ...]] = (0.0, 0.2, 0.4, 0.6, 0.8, 1.0),
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compression_ratio_threshold: Optional[float] = 2.4,
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compression_ratio_halucination_threshold: Optional[float] = 3,
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logprob_threshold: Optional[float] = -1.0,
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no_speech_threshold: Optional[float] = 0.6,
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condition_on_previous_text: bool = True,
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initial_prompt: Optional[str] = None,
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carry_initial_prompt: bool = False,
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word_timestamps: bool = False,
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prepend_punctuations: str = "\"'“¿([{-",
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append_punctuations: str = "\"'.。,,!!??::”)]}、",
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@ -76,6 +76,9 @@ def transcribe(
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compression_ratio_threshold: float
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If the gzip compression ratio is above this value, treat as failed
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compression_ratio_halcination_threshold: float
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If the gzip compression ratio is above this value after all attempts to decode, treat as a halucination and skip
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logprob_threshold: float
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If the average log probability over sampled tokens is below this value, treat as failed
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@ -205,7 +208,7 @@ def transcribe(
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compression_ratio_threshold is not None
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and decode_result.compression_ratio > compression_ratio_threshold
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):
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needs_fallback = True # too repetitive
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needs_fallback = True # too repetitive <-- We can inprove it...
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if (
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logprob_threshold is not None
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and decode_result.avg_logprob < logprob_threshold
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@ -216,6 +219,13 @@ def transcribe(
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and decode_result.no_speech_prob > no_speech_threshold
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):
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needs_fallback = False # silence
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if (
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compression_ratio_halucination_threshold is not None
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and decode_result.compression_ratio > compression_ratio_halucination_threshold
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and t == temperatures[-1]
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):
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# Discard the segment
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continue # Skip to the next segment
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if not needs_fallback:
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break
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