| import gradio as gr | |
| title = "FastSpeech2" | |
| description = "Gradio Demo for fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit. To use it, simply add your text, or click one of the examples to load them. Read more at the links below." | |
| article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2109.06912' target='_blank'>fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit</a> | <a href='https://github.com/pytorch/fairseq/tree/main/examples/speech_synthesis' target='_blank'>Github Repo</a></p>" | |
| examples = [ | |
| ["Hello, this is a test run.","fastspeech2-en-200_speaker-cv4"] | |
| ] | |
| io1 = gr.Interface.load("huggingface/facebook/fastspeech2-en-200_speaker-cv4") | |
| io2 = gr.Interface.load("huggingface/facebook/fastspeech2-en-ljspeech") | |
| def inference(text, model): | |
| if model == "fastspeech2-en-200_speaker-cv4": | |
| audio = io1(text) | |
| else: | |
| audio = io2(text) | |
| return audio | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Textbox(label="Input", lines=10),gr.inputs.Dropdown(choices=["fastspeech2-en-200_speaker-cv4","fastspeech2-en-ljspeech"], type="value", default="prophetnet-large-uncased", label="model") | |
| ], | |
| gr.outputs.Audio(label="Output"), | |
| examples=examples, | |
| article=article, | |
| title=title, | |
| description=description).launch(enable_queue=True, cache_examples=True) | |