Create app.py

app.py

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+import librosa
+import gradio as gr
+import pedalboard
+import soundfile as sf
+
+def inference(audio):
+    y, sr = librosa.load(audio.name, sr=44100)
+
+    reverb = pedalboard.Reverb()
+    reverb
+    reverb.room_size
+    reverb.wet_level = 1.0
+    effected = reverb(y, sample_rate=sr)
+    with sf.SoundFile('./processed-output-stereo.wav', 'w', samplerate=sr, channels=len(effected.shape)) as f:
+        f.write(effected)
+    return './processed-output-stereo.wav'
+
+
+inputs = gr.inputs.Audio(label="Input Audio", type="file")
+outputs =  gr.outputs.Audio(label="Output Audio", type="file")
+
+
+title = "VITS"
+description = "demo for VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech. 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/2106.06103'>Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech</a> | <a href='https://github.com/jaywalnut310/vits'>Github Repo</a></p>"
+
+
+gr.Interface(inference, inputs, outputs, title=title, description=description, article=article).launch(debug=True)