diff options
Diffstat (limited to 'app/hallucination_filter.py')
| -rw-r--r-- | app/hallucination_filter.py | 47 |
1 files changed, 28 insertions, 19 deletions
diff --git a/app/hallucination_filter.py b/app/hallucination_filter.py index 9b24a85..fa7b16a 100644 --- a/app/hallucination_filter.py +++ b/app/hallucination_filter.py @@ -4,16 +4,23 @@ from logger import log, log_err import numpy as np import pandas as pd from pathlib import Path +import pronouncing +import re import sys - +def count_syllables(word): + """Count syllables in a word using pronouncing library with regex fallback.""" + phones = pronouncing.phones_for_word(word.lower()) + return pronouncing.syllable_count(phones[0]) +def text_syllable_count(text): + """Count total syllables in text.""" + words = re.findall(r'\b\w+\b', text) + return sum(count_syllables(word) for word in words) class HallucinationFilter: """Filter for detecting hallucinated segments in speech-to-text output.""" - def __init__(self, model_path: Path = None): """ Initialize the hallucination filter. - Args: model_path: Optional path to the model file. If not provided, uses the default path. @@ -21,46 +28,48 @@ class HallucinationFilter: self.model = None self.threshold = None self.features = None - # Get the project root directory app_root = Path(__file__).resolve().parent project_root = app_root.parent - # Use provided path or default if model_path is None: model_path = project_root / "Models" / "thankyou_filter_gb.pkl" - # Try to load the model log_err(f"Loading hallucination filter") bundle = joblib.load(model_path) self.model = bundle["model"] self.threshold = bundle["threshold"] - self.features = bundle["features"] # Extract feature names + self.features = bundle["features"] log_err(f"Loaded hallucination filter model from {model_path}") - - def is_thank_you_hallucination(self, segment) -> bool: + def is_hallucination(self, segment) -> bool: """ - Check if a segment is likely a "Thank you" hallucination. + Check if a segment is likely a hallucination. Returns False if model is not available. - Args: segment: A segment object with attributes avg_logprob, audio_len_s, - no_speech_prob, and compression_ratio. - + no_speech_prob, compression_ratio, text, start, and end. Returns: bool: True if the segment is likely a hallucination, False otherwise. """ - # Create DataFrame with proper feature names + # Calculate text-based features + text = getattr(segment, 'text', '') + duration = segment.audio_len_s + raw_duration = segment.end_ts - segment.start_ts + n_syllables = text_syllable_count(text) + sps = n_syllables / duration + raw_sps = n_syllables / raw_duration + duration_ratio = raw_duration / duration X = pd.DataFrame([[ segment.avg_logprob, - segment.audio_len_s, segment.no_speech_prob, segment.compression_ratio, - np.log1p(segment.audio_len_s), - segment.avg_logprob * segment.audio_len_s + np.log1p(duration), + np.log1p(sps), + np.log1p(raw_duration), + np.log1p(raw_sps), + duration_ratio, + segment.avg_logprob * duration ]], columns=self.features) - # Get probability prob = self.model.predict_proba(X)[0, 1] return prob >= self.threshold - |