select default channel 0

app.py

@@ -0,0 +1,75 @@
+import gradio as gr
+import re
+import subprocess
+import math
+import shutil
+import soundfile as sf
+import tempfile
+import os
+import requests
+import time
+
+
+def _return_yt_html_embed(yt_url):
+    video_id = yt_url.split("?v=")[-1]
+    HTML_str = (
+        f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
+        " </center>"
+    )
+    return HTML_str
+
+
+def transcribe_base(audio, language):
+    start_time = time.time()
+
+    d, sr = sf.read(audio)
+    if len(d.shape) == 2:
+        d = d[:,0]
+    data = {'audio': d.tolist(),
+            'sampling_rate': sr,
+            'language': language}
+    print(data)
+    response = requests.post(os.getenv("api_url"), json=data).json()
+    result = response["text"]
+
+    end_time = time.time()
+    print("-"*50)
+    print(len(data["audio"])/float(sr))
+    print(end_time-start_time)
+    print("-"*50)
+
+    return result
+
+
+def transcribe(audio_microphone, audio_upload, language):
+    print("Transcription request")
+    print(audio_microphone, audio_upload, language)
+    audio = audio_microphone if audio_microphone is not None else audio_upload
+    return transcribe_base(audio, language)
+
+
+demo = gr.Blocks()
+with demo:
+    gr.Markdown("# Speech recognition using Whisper models")
+    gr.Markdown("Orai NLP Technologies")
+
+    with gr.Tab("Trancribe Audio"):
+        iface = gr.Interface(
+            fn=transcribe,
+            inputs=[
+                gr.Audio(sources="microphone", type="filepath"),
+                gr.Audio(sources="upload", type="filepath"),
+                gr.Dropdown(choices=[("Basque", "eu"),
+                                     ("Spanish", "es"),
+                                     ("English", "en")],
+                                     #("French", "fr"),
+                                     #("Italian", "it"),
+                            value="eu")
+            ],
+            outputs=[
+                gr.Textbox(label="Transcription", autoscroll=False)
+            ],
+            allow_flagging="never",
+        )
+demo.queue(max_size=1)
+demo.launch(share=False, max_threads=3, auth=(os.getenv("username"), os.getenv("password")), auth_message="Please provide a username and a password.")