Ritesh-hf commited on
Commit
7f79518
·
verified ·
1 Parent(s): cfdb71d

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +29 -10
app.py CHANGED
@@ -7,15 +7,15 @@ from pydub import AudioSegment
7
  from pydub.generators import Sine
8
  import io
9
 
10
- MODEL_NAME = "openai/whisper-tiny"
11
  BATCH_SIZE = 8
12
- # device = 0 if torch.cuda.is_available() else "cpu"
13
 
14
  pipe = pipeline(
15
  task="automatic-speech-recognition",
16
  model=MODEL_NAME,
17
  chunk_length_s=30,
18
- # device=device,
19
  )
20
 
21
  arabic_bad_Words = pd.read_csv("arabic_bad_words_dataset.csv")
@@ -23,14 +23,11 @@ english_bad_Words = pd.read_csv("english_bad_words_dataset.csv")
23
 
24
 
25
  def clean_english_word(word):
26
- # Use regex to remove special characters, punctuation, and spaces around words
27
  cleaned_text = re.sub(r'^[\s\W_]+|[\s\W_]+$', '', word)
28
- return cleaned_text
29
 
30
  def clean_arabic_word(word):
31
- # Define a regex pattern to match any non-Arabic letter character
32
  pattern = r'[^\u0600-\u06FF]'
33
- # Replace any character matching the pattern with an empty string
34
  cleaned_word = re.sub(pattern, '', word)
35
  return cleaned_word
36
 
@@ -43,14 +40,15 @@ def classifier(word_list_with_timestamp, language):
43
  list_to_search = set(english_bad_Words["words"])
44
  for item in word_list_with_timestamp:
45
  word = clean_english_word(item['text'])
46
- if word in list_to_search:
47
  foul_words.append(word)
48
  negative_timestamps.append(item['timestamp'])
 
49
  else:
50
  list_to_search = list(arabic_bad_Words["words"])
51
  for item in word_list_with_timestamp:
52
  word = clean_arabic_word(item['text'])
53
- for word_in_list in list_to_search:
54
  if word_in_list == word:
55
  foul_words.append(word)
56
  negative_timestamps.append(item['timestamp'])
@@ -65,7 +63,6 @@ def generate_bleep(duration_ms, frequency=1000):
65
 
66
  def mute_audio_range(audio_filepath, ranges, bleep_frequency=800):
67
  audio = AudioSegment.from_file(audio_filepath)
68
-
69
  for range in ranges:
70
  start_time = range[0] - 0.1
71
  end_time = range[-1] + 0.1
@@ -123,10 +120,32 @@ examples = [
123
  ["arabic_english_audios/audios/arabic_hate_audio_1.mp3", 'Arabic', 'transcribe', 'word'],
124
  ["arabic_english_audios/audios/arabic_hate_audio_2.flac", 'Arabic', 'transcribe', 'word'],
125
  ["arabic_english_audios/audios/arabic_hate_audio_3.flac", 'Arabic', 'transcribe', 'word'],
 
 
126
  ["arabic_english_audios/audios/english_audio_1.wav", 'English', 'transcribe', 'word'],
127
  ["arabic_english_audios/audios/english_audio_2.mp3", 'English', 'transcribe', 'word'],
128
  ["arabic_english_audios/audios/english_audio_3.mp3", 'English', 'transcribe', 'word'],
 
 
 
 
 
 
 
 
 
 
 
129
  ["arabic_english_audios/audios/english_audio_4.mp3", 'English', 'transcribe', 'word'],
 
 
 
 
 
 
 
 
 
130
  ["arabic_english_audios/audios/english_audio_5.mp3", 'English', 'transcribe', 'word'],
131
  ["arabic_english_audios/audios/english_audio_6.wav", 'English', 'transcribe', 'word']
132
  ]
 
7
  from pydub.generators import Sine
8
  import io
9
 
10
+ MODEL_NAME = "openai/whisper-large-v3"
11
  BATCH_SIZE = 8
12
+ device = 0 if torch.cuda.is_available() else "cpu"
13
 
14
  pipe = pipeline(
15
  task="automatic-speech-recognition",
16
  model=MODEL_NAME,
17
  chunk_length_s=30,
18
+ device=device,
19
  )
20
 
21
  arabic_bad_Words = pd.read_csv("arabic_bad_words_dataset.csv")
 
23
 
24
 
25
  def clean_english_word(word):
 
26
  cleaned_text = re.sub(r'^[\s\W_]+|[\s\W_]+$', '', word)
27
+ return cleaned_text.lower()
28
 
29
  def clean_arabic_word(word):
 
30
  pattern = r'[^\u0600-\u06FF]'
 
31
  cleaned_word = re.sub(pattern, '', word)
32
  return cleaned_word
33
 
 
40
  list_to_search = set(english_bad_Words["words"])
41
  for item in word_list_with_timestamp:
42
  word = clean_english_word(item['text'])
43
+ if word.lower() in list_to_search:
44
  foul_words.append(word)
45
  negative_timestamps.append(item['timestamp'])
46
+ break
47
  else:
48
  list_to_search = list(arabic_bad_Words["words"])
49
  for item in word_list_with_timestamp:
50
  word = clean_arabic_word(item['text'])
51
+ for word in list_to_search:
52
  if word_in_list == word:
53
  foul_words.append(word)
54
  negative_timestamps.append(item['timestamp'])
 
63
 
64
  def mute_audio_range(audio_filepath, ranges, bleep_frequency=800):
65
  audio = AudioSegment.from_file(audio_filepath)
 
66
  for range in ranges:
67
  start_time = range[0] - 0.1
68
  end_time = range[-1] + 0.1
 
120
  ["arabic_english_audios/audios/arabic_hate_audio_1.mp3", 'Arabic', 'transcribe', 'word'],
121
  ["arabic_english_audios/audios/arabic_hate_audio_2.flac", 'Arabic', 'transcribe', 'word'],
122
  ["arabic_english_audios/audios/arabic_hate_audio_3.flac", 'Arabic', 'transcribe', 'word'],
123
+ ["arabic_english_audios/audios/arabic_hate_audio_31.mp3", 'Arabic', 'transcribe', 'word'],
124
+ ["arabic_english_audios/audios/arabic_hate_audio_32.mp3", 'Arabic', 'transcribe', 'word'],
125
  ["arabic_english_audios/audios/english_audio_1.wav", 'English', 'transcribe', 'word'],
126
  ["arabic_english_audios/audios/english_audio_2.mp3", 'English', 'transcribe', 'word'],
127
  ["arabic_english_audios/audios/english_audio_3.mp3", 'English', 'transcribe', 'word'],
128
+
129
+ ["arabic_english_audios/audios/english_audio_31.mp3", 'English', 'transcribe', 'word'],
130
+ ["arabic_english_audios/audios/english_audio_32.mp3", 'English', 'transcribe', 'word'],
131
+ ["arabic_english_audios/audios/english_audio_33.mp3", 'English', 'transcribe', 'word'],
132
+ ["arabic_english_audios/audios/english_audio_34.mp3", 'English', 'transcribe', 'word'],
133
+ ["arabic_english_audios/audios/english_audio_35.mp3", 'English', 'transcribe', 'word'],
134
+ ["arabic_english_audios/audios/english_audio_36.mp3", 'English', 'transcribe', 'word'],
135
+ ["arabic_english_audios/audios/english_audio_37.mp3", 'English', 'transcribe', 'word'],
136
+ ["arabic_english_audios/audios/english_audio_38.mp3", 'English', 'transcribe', 'word'],
137
+ ["arabic_english_audios/audios/english_audio_39.mp3", 'English', 'transcribe', 'word'],
138
+ ["arabic_english_audios/audios/english_audio_40.mp3", 'English', 'transcribe', 'word'],
139
  ["arabic_english_audios/audios/english_audio_4.mp3", 'English', 'transcribe', 'word'],
140
+ ["arabic_english_audios/audios/english_audio_41.mp3", 'English', 'transcribe', 'word'],
141
+ ["arabic_english_audios/audios/english_audio_42.mp3", 'English', 'transcribe', 'word'],
142
+ ["arabic_english_audios/audios/english_audio_43.mp3", 'English', 'transcribe', 'word'],
143
+ ["arabic_english_audios/audios/english_audio_44.mp3", 'English', 'transcribe', 'word'],
144
+ ["arabic_english_audios/audios/english_audio_45.mp3", 'English', 'transcribe', 'word'],
145
+ ["arabic_english_audios/audios/english_audio_46.mp3", 'English', 'transcribe', 'word'],
146
+ ["arabic_english_audios/audios/english_audio_48.mp3", 'English', 'transcribe', 'word'],
147
+ ["arabic_english_audios/audios/english_audio_49.mp3", 'English', 'transcribe', 'word'],
148
+
149
  ["arabic_english_audios/audios/english_audio_5.mp3", 'English', 'transcribe', 'word'],
150
  ["arabic_english_audios/audios/english_audio_6.wav", 'English', 'transcribe', 'word']
151
  ]