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f74654d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | import os
import shutil
from pydub import AudioSegment
RAVDESS_MAP = {
'01': 'neutral', '02': 'calm', '03': 'happiness', '04': 'sadness',
'05': 'anger', '06': 'fear', '07': 'disgust', '08': 'surprise'
}
KNOWN_EMOTIONS = ['anger', 'neutral', 'sadness', 'happiness', 'fear', 'disgust', 'surprise', 'calm']
# Handling some common synonyms/variations
EMOTION_ALIASES = {
'happy': 'happiness',
'sad': 'sadness',
'angry': 'anger',
'surprised': 'surprise'
}
def convert_to_wav(source_path, target_path):
"""Converts audio file to WAV format."""
try:
audio = AudioSegment.from_file(source_path)
audio.export(target_path, format="wav")
return True
except Exception as e:
print(f"Error converting {source_path}: {e}")
return False
def get_label_from_filename(filename):
"""Extracts emotion label from filename based on patterns."""
filename = os.path.basename(filename).lower()
# Rule 1: RAVDESS dataset (e.g., 03-01-01-01-01-01-01.wav)
if filename.count('-') == 6 and filename.startswith('03'):
parts = filename.replace('.wav', '').split('-')
if len(parts) > 2:
return RAVDESS_MAP.get(parts[2])
# Rule 2: General emotion words
# Check for exact matches or surrounded by underscores/dots
for emotion in KNOWN_EMOTIONS + list(EMOTION_ALIASES.keys()):
# Simple containment check might be too loose (e.g., "fearless"),
# but matches the original script's logic roughly.
# Improving it with delimiters for safety.
patterns = [
f"_{emotion}_",
f"{emotion}_",
f"_{emotion}.",
f"upload_{emotion}_"
]
# Also check if it STARTS with the emotion (common in some datasets)
if filename.startswith(f"{emotion}_") or any(p in filename for p in patterns):
normalized = EMOTION_ALIASES.get(emotion, emotion)
return normalized
return None
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