update descriptions

app.py

@@ -21,6 +21,7 @@ from data.tokenizer import (
 from data.collation import get_text_token_collater
 from models.vallex import VALLE
 from utils.g2p import PhonemeBpeTokenizer
+from descriptions import *
 
 import gradio as gr
 import whisper
@@ -305,14 +306,16 @@ def infer_from_prompt(text, language, accent, prompt_file):
 def main():
     app = gr.Blocks()
     with app:
+        gr.Markdown(top_md)
         with gr.Tab("Infer from audio"):
+            gr.Markdown(infer_from_audio_md)
             with gr.Row():
                 with gr.Column():
 
                     textbox = gr.TextArea(label="Text",
                                           placeholder="Type your sentence here",
                                           value="VALLEX can synthesize personalized speech in another language for a monolingual speaker.", elem_id=f"tts-input")
-                    language_dropdown = gr.Dropdown(choices=['English', '中文', '日本語', 'mix'], value='English', label='language')
+                    language_dropdown = gr.Dropdown(choices=['English', '中文', '日本語'], value='English', label='language')
                     accent_dropdown = gr.Dropdown(choices=['no-accent', 'English', '中文', '日本語'], value='no-accent', label='accent')
                     upload_audio_prompt = gr.Audio(label='uploaded audio prompt', source='upload', interactive=True)
                     record_audio_prompt = gr.Audio(label='recorded audio prompt', source='microphone', interactive=True)
@@ -332,6 +335,7 @@ def main():
                                 inputs=[textbox_mp, upload_audio_prompt, record_audio_prompt],
                                 outputs=[text_output, prompt_output])
         with gr.Tab("Make prompt"):
+            gr.Markdown(make_prompt_md)
             with gr.Row():
                 with gr.Column():
                     textbox2 = gr.TextArea(label="Prompt name",
@@ -347,12 +351,13 @@ def main():
                               inputs=[textbox2, upload_audio_prompt_2, record_audio_prompt_2],
                               outputs=[text_output_2, prompt_output_2])
         with gr.Tab("Infer from prompt"):
+            gr.Markdown(infer_from_prompt_md)
             with gr.Row():
                 with gr.Column():
                     textbox_3 = gr.TextArea(label="Text",
                                           placeholder="Type your sentence here",
                                           value="VALLEX can synthesize personalized speech in another language for a monolingual speaker.", elem_id=f"tts-input")
-                    language_dropdown_3 = gr.Dropdown(choices=['English', '中文', '日本語', 'mix'], value='English',
+                    language_dropdown_3 = gr.Dropdown(choices=['English', '中文', '日本語'], value='English',
                                                     label='language')
                     accent_dropdown_3 = gr.Dropdown(choices=['no-accent', 'English', '中文', '日本語'], value='no-accent',
                                                   label='accent')

descriptions.py

@@ -0,0 +1,25 @@
+top_md = """
+# VALL-E X  
+Unofficial implementation of Microsoft's [VALL-E X](https://arxiv.org/pdf/2303.03926).<br>
+VALL-E X can synthesize high-quality personalized speech with only a 3-second enrolled recording of 
+an unseen speaker as an acoustic prompt, even in another language for a monolingual speaker.<br>
+This implementation supports zero-shot, mono-lingual/cross-lingual text-to-speech functionality of three languages (English, Chinese, Japanese)<br>  
+See this [demo](https://plachtaa.github.io/) page for more details.
+"""
+
+infer_from_audio_md = """
+Upload a speech of 3~10 seconds as the audio prompt and type in the text you'd like to synthesize.<br>
+The model will synthesize speech of given text with the same voice of your audio prompt.<br>
+The model also tends to preserve the emotion & acoustic environment of your given speech.<br>
+For faster inference, please use **"Make prompt"** to get a `.npz` file as the encoded audio prompt, and use it by **"Infer from prompt"**
+"""
+
+make_prompt_md = """
+Upload a speech of 3~10 seconds as the audio prompt.<br>
+Get a `.npz` file as the encoded audio prompt. Use it by **"Infer with prompt"**
+"""
+
+infer_from_prompt_md = """
+Faster than **"Infer from audio"**.<br>
+You need to **"Make prompt"** first, and upload the encoded prompt (a `.npz` file)
+"""