diff --git a/subgen.py b/subgen.py
index ba6dcb0..46e7aa1 100644
--- a/subgen.py
+++ b/subgen.py
@@ -60,6 +60,7 @@ reload_script_on_change = convert_to_bool(os.getenv('RELOAD_SCRIPT_ON_CHANGE', F
 model_prompt = os.getenv('USE_MODEL_PROMPT', 'False')
 custom_model_prompt = os.getenv('CUSTOM_MODEL_PROMPT', '')
 lrc_for_audio_files = convert_to_bool(os.getenv('LRC_FOR_AUDIO_FILES', True))
+custom_regroup = os.getenv('CUSTOM_REGROUP', 'cm_sl=84_sl=42++++++1')
 
 if transcribe_device == "gpu":
     transcribe_device = "cuda"
@@ -335,9 +336,12 @@ def asr(
         start_model()
         files_to_transcribe.insert(0, f"Bazarr-asr-{random_name}")
         audio_data = np.frombuffer(audio_file.file.read(), np.int16).flatten().astype(np.float32) / 32768.0
-        if(model_prompt):
+        if model_prompt:
             custom_model_prompt = greetings_translations.get(language, '') or custom_model_prompt
-        result = model.transcribe_stable(audio_data, task=task, input_sr=16000, language=language, progress_callback=progress, initial_prompt=custom_model_prompt)
+        if custom_regroup:
+            result = model.transcribe_stable(audio_data, task=task, input_sr=16000, language=language, progress_callback=progress, initial_prompt=custom_model_prompt, regroup=custom_regroup)
+        else:
+            result = model.transcribe_stable(audio_data, task=task, input_sr=16000, language=language, progress_callback=progress, initial_prompt=custom_model_prompt)
         appendLine(result)
         elapsed_time = time.time() - start_time
         minutes, seconds = divmod(int(elapsed_time), 60)
@@ -448,7 +452,10 @@ def gen_subtitles(file_path: str, transcribe_or_translate: str, front=True, forc
             if force_detected_language_to:
                 forceLanguage = force_detected_language_to
                 logging.info(f"Forcing language to {forceLanguage}")
-            result = model.transcribe_stable(file_path, language=forceLanguage, task=transcribe_or_translate, progress_callback=progress, initial_prompt=custom_model_prompt)
+            if custom_regroup:
+                result = model.transcribe_stable(file_path, language=forceLanguage, task=transcribe_or_translate, progress_callback=progress, initial_prompt=custom_model_prompt, regroup=custom_regroup)
+            else:
+                result = model.transcribe_stable(file_path, language=forceLanguage, task=transcribe_or_translate, progress_callback=progress, initial_prompt=custom_model_prompt)
             appendLine(result)
             file_name, file_extension = os.path.splitext(file_path)
             if isAudioFileExtension(file_extension) and lrc_for_audio_files: