Update modules/whisper/whisper_base.py

modules/whisper/whisper_base.py

@@ -413,13 +413,13 @@ class WhisperBase(ABC):
                 title_line = ""
                 if add_timestamp_preview: title_line += "□"
                 if diarize_speakers: title_line += "□"
-                title_line += f'**Media file:\t{info["input_source_file"]}'
+                title_line += f'Media file:\t{info["input_source_file"]}'
                 title_line += f'\nLanguage:\t{info["lang"]} (probability {info["lang_prob"]}%)'
                 if params.is_translate: title_line += f'\nTranslation:\t{info["transcription"]} (Handled by OpenAI Whisper)'
                 if translate_output: title_line += f'\nTranslation:\t{info["translation"]} (Handled by Facebook NLLB)'
                 title_line += "■"
 
-                temp_subtitle = info["subtitle"].rstrip("\n")
+                temp_subtitle = info["subtitle"]
                 temp_subtitle = temp_subtitle.replace("\t","□")
                 temp_subtitle = temp_subtitle.replace("\n","■")
                 total_result += title_line+temp_subtitle
@@ -430,7 +430,7 @@ class WhisperBase(ABC):
             #total_info += f"Total processing time:\t{self.format_time((time_end-time_start).total_seconds())}"
             total_info = f"Processed {file_count} {'file' if file_count == 1 else 'files'} in {self.format_time((time_end-time_start).total_seconds())}"
             
-            result_str = self.transform_text_to_list(total_result,"□","■")
+            result_str = self.transform_text_to_list(total_result.rstrip("\n"),"□","■") #Transform to gr.Dataframe format
             result_file_path = [info['path'] for info in files_to_download.values()]
 
             return [result_str,result_file_path,total_info]