import gradio as gr import numpy as np # from audioldm import text_to_audio def text2audio(text, length): # waveform = text_to_audio(text, n_gen=1) # [bs, 1, samples] # waveform = [(16000, wave[0]) for wave in waveform] waveform = [(16000, np.random.randn(16000)), (16000, np.random.randn(16000))] return waveform # iface = gr.Interface(fn=greet, inputs="text", outputs=["audio", "audio"]) # iface.launch() block = gr.Blocks() with block: gr.HTML( """

Text-to-Audio Generation with AudioLDM

[Paper] [Project page]

""" ) with gr.Group(): with gr.Box(): textbox = gr.Textbox(value="A man is speaking in a huge room") length = gr.Slider(1.0, 30.0, value=5.0, step=0.5, label="Audio length in seconds") # model = gr.Dropdown(choices=["harmonai/maestro-150k"], value="harmonai/maestro-150k",type="value", label="Model") out = [gr.Audio(label="Output", type="numpy"), gr.Audio(label="Output", type="numpy")] btn = gr.Button("Submit").style(full_width=True) btn.click(text2audio, inputs=[textbox, length], outputs=out) gr.HTML(''' ''') block.launch(debug=True)