[demo] Initialize the first version

app.py

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+
+import json
+import gradio as gr
+import numpy as np
+import wenetruntime as wenet
+
+wenet.set_log_level(2)
+decoder = wenet.Decoder(lang='chs')
+
+
+def recognition(audio):
+    print(audio)
+    if audio is None:
+        return "Input Error! Please enter one audio!"
+    sr, y = audio
+    assert sr in [48000, 16000]
+    if sr == 48000:  # Optional resample to 16000
+        y = (y / max(np.max(y), 1) * 32767)[::3].astype("int16")
+    ans = decoder.decode(y.tobytes(), True)
+    if ans == None:
+        return "ERROR! No text output! Please try again!"
+    # ans (json)
+    # {
+    #    'nbest' : [{"sentence" : ""}], 'type' : 'final_result
+    # }
+    ans = json.loads(ans)
+    print(ans)
+    txt = ans['nbest'][0]['sentence']
+    return txt
+
+
+# input
+inputs = [
+    gr.inputs.Audio(source="microphone",
+                    type="numpy",
+                    label='Speaker#1')
+]
+
+output = gr.outputs.Textbox(label="Output Text")
+
+# examples = ['examples/BAC009S0764W0121.wav']
+text = "Speech Recognition in WeNet | 基于 WeNet 的语音识别"
+
+# description
+description = ("WeSpeaker Demo ! Try it with your own voice !")
+
+article = (
+    "<p style='text-align: center'>"
+    "<a href='https://github.com/wenet-e2e/wespeaker' target='_blank'>Github: Learn more about WeSpeaker</a>"
+    "</p>")
+
+interface = gr.Interface(
+    fn=recognition,
+    inputs=inputs,
+    outputs=output,
+    title=text,
+    description=description,
+    article=article,
+    theme='huggingface',
+)
+
+interface.launch(enable_queue=True)

requirements.txt

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+wenetruntime
+gradio