update source_languages

app.py

@@ -29,8 +29,8 @@ import psutil
 
 whisper_models = ["tiny", "base", "small", "medium", "large-v1", "large-v2"]
 source_languages = {
-    "Indonesia": "Indonesian",
-    "English": "English",
+    "id": "Indonesian",
+    "en": "English",
     "zh": "Chinese",
     "de": "German",
     "es": "Spanish",
@@ -46,7 +46,8 @@ source_languages = {
     "ar": "Arabic",
     "sv": "Swedish",
     "it": "Italian",
-     "hi": "Hindi",
+   
+    "hi": "Hindi",
     "fi": "Finnish",
     "vi": "Vietnamese",
     "he": "Hebrew",
@@ -351,7 +352,7 @@ video_in = gr.Video(label="Video file", mirror_webcam=False)
 youtube_url_in = gr.Textbox(label="Youtube url", lines=1, interactive=True)
 df_init = pd.DataFrame(columns=['Start', 'End', 'Speaker', 'Text'])
 memory = psutil.virtual_memory()
-selected_source_lang = gr.Dropdown(choices=source_language_list, type="value", value="en", label="Spoken language in video", interactive=True)
+selected_source_lang = gr.Dropdown(choices=source_language_list, type="value", value="id", label="Spoken language in video", interactive=True)
 selected_whisper_model = gr.Dropdown(choices=whisper_models, type="value", value="base", label="Selected Whisper model", interactive=True)
 number_speakers = gr.Number(precision=0, value=0, label="Input number of speakers for better results. If value=0, model will automatic find the best number of speakers", interactive=True)
 system_info = gr.Markdown(f"*Memory: {memory.total / (1024 * 1024 * 1024):.2f}GB, used: {memory.percent}%, available: {memory.available / (1024 * 1024 * 1024):.2f}GB*")