| import gradio as gr | |
| import subprocess | |
| predefined_texts = [ | |
| "A combination of Canadian capital quickly organized and petitioned for the same privileges.", | |
| "The date was nearly eighteen years old.", | |
| "Hardly were our plans made public before we were met by powerful opposition.", | |
| ] | |
| emotion_mapping = {"amused": 0, "anger": 1, | |
| "disgust": 2, "neutral": 3, "sleepiness": 4} | |
| def synthesize_speech(input_type, text, own_text, speaker_id, embed_type, emotion_id): | |
| if input_type == "Choose from examples": | |
| selected_text = text | |
| else: | |
| selected_text = own_text | |
| if embed_type == "bert_embed": | |
| command = f"python3 synthesize.py --text '{selected_text}' --bert_embed 1 --speaker_id {speaker_id} --restore_step 900000 --mode single -p config/EmoV_DB/preprocess.yaml -m config/EmoV_DB/model.yaml -t config/EmoV_DB/train.yaml" | |
| else: | |
| command = f"python3 synthesize.py --text '{selected_text}' --emotion_id {emotion_mapping[emotion_id]} --speaker_id {speaker_id} --restore_step 900000 --mode single -p config/EmoV_DB/preprocess.yaml -m config/EmoV_DB/model.yaml -t config/EmoV_DB/train.yaml" | |
| output = subprocess.check_output(command, shell=True) | |
| audio_file = f'output/result/EmoV_DB/{selected_text}.wav' | |
| return audio_file | |
| iface = gr.Interface( | |
| fn=synthesize_speech, | |
| inputs=[ | |
| gr.inputs.Radio( | |
| ["Choose from examples", "Enter your own text"], label="Input Type"), | |
| gr.inputs.Dropdown(choices=predefined_texts, label="Select a text"), | |
| gr.inputs.Textbox(lines=2, label="Enter your own text"), | |
| gr.inputs.Slider(minimum=0, maximum=3, step=1, | |
| default=0, label="Speaker ID"), | |
| gr.inputs.Radio(["bert_embed", "emotion_id"], label="Embedding Type"), | |
| gr.inputs.Dropdown(choices=emotion_mapping, label="Select Emotion"), | |
| ], | |
| outputs=gr.outputs.Audio(type="filepath"), | |
| title="Text-to-Speech Demo", | |
| ) | |
| iface.launch() | |