From 55b82fddc9283475acbf87abcbddae79a2038035 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Kristofer=20Rolf=20S=C3=B6derstr=C3=B6m?=
 <kristofer.soderstrom@gmail.com>
Date: Wed, 22 Mar 2023 11:38:51 +0100
Subject: [PATCH] Create transcribe.py

---
 transcribe.py | 52 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 transcribe.py

diff --git a/transcribe.py b/transcribe.py
new file mode 100644
index 0000000..08ebf69
--- /dev/null
+++ b/transcribe.py
@@ -0,0 +1,52 @@
+import whisper 
+import glob, os
+
+def transcribe(path, file_type, model='base', language=None, verbose=True):
+  '''Implementation of OpenAI's whisper model. Downloads model, transcribes audio files
+  in a folder and returns the text files with transcriptions.'''
+    
+    try:
+        os.mkdir('{}transcriptions'.format(path))
+    except FileExistsError:
+        pass
+    
+    glob_file = glob.glob(path+'/*{}'.format(file_type))
+    path = path
+    
+    print('Using {} model, you can change this by specifying model="medium" for example'.format(model))
+    print('Only looking for file type {}, you can change this by specifying file_type="mp3"'.format(file_type))    
+    print('Expecting {} language, you can change this by specifying language="English". None will try to auto-detect'.format(language))
+    print('Verbosity is {}. If TRUE it will print out the text as it is transcribed, you can turn this off by setting verbose=False'.format(verbose))
+    print('\nThere are {} {} files in path: {}\n\n'.format(len(glob_file), file_type, path))
+    print('Loading model...')
+    model = whisper.load_model(model)
+    
+    
+    
+    for idx,file in enumerate(glob_file):
+        title = os.path.basename(file).split('.')[0]
+        
+        print('Transcribing file number number {}: {}'.format(idx+1,file))
+        print('Model and file loaded...\nStarting transcription...\n')
+        result = model.transcribe(
+            file, 
+            language=language, 
+            verbose=True
+        )
+        start=[]
+        end=[]
+        text=[]
+        for i in range(len(result['segments'])):
+            start.append(result['segments'][i]['start'])
+            end.append(result['segments'][i]['end'])
+            text.append(result['segments'][i]['text'])
+        
+        with open("{}transcriptions/{}.txt".format(path,title), 'w', encoding='utf-8') as file:
+            file.write(title)
+            file.write('\nIn seconds:')
+            for i in range(len(result['segments'])):
+                file.writelines('\n[{:.2f} --> {:.2f}]:{}'.format(start[i], end[i], text[i]))
+                
+        print('\nFinished file number {}.\n\n\n'.format(idx+1))
+
+    return 'Finished transcription, files can be found in {}'.format(path)