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import gradio as gr | |
import numpy as np | |
from datasets import load_dataset | |
speech_commands = load_dataset("speech_commands", "v0.02", split="test") | |
id2label = speech_commands.features["label"].int2str | |
def generate_audio(): | |
example = speech_commands.shuffle()[0] | |
audio = example["audio"] | |
return (audio["sampling_rate"], (audio["array"] * 32_767).astype(np.int16)), id2label(example["label"]) | |
with gr.Blocks() as demo: | |
with gr.Column(): | |
for _ in range(4): | |
audio, label = generate_audio() | |
output = gr.Audio(audio, label=label) | |
demo.launch() |