| import gradio as gr | |
| import subprocess | |
| predefined_texts = ["Example text 1", "Example text 2", "Example text 3"] | |
| def synthesize_speech(text, speaker_id): | |
| command = f"python3 synthesize.py --text '{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" | |
| output = subprocess.check_output(command, shell=True) | |
| # Replace this with the path of the generated audio file | |
| audio_file = 'output_file_path' | |
| return audio_file | |
| iface = gr.Interface(fn=synthesize_speech, | |
| inputs=[gr.inputs.Dropdown(choices=predefined_texts, label="Select a text"), | |
| gr.inputs.Slider(minimum=0, maximum=10, step=1, default=0, label="Speaker ID")], | |
| outputs=gr.outputs.Audio(type="file"), | |
| title="Text-to-Speech Demo") | |
| iface.launch() | |