Create app.py

app.py

@@ -0,0 +1,28 @@
+import time
+from transformers import pipeline
+import gradio as gr
+import numpy as np
+import librosa
+
+pipe2 = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec-hindi")
+
+def resample_to_16k(audio, orig_sr):
+    y_resampled = librosa.resample(y=audio, orig_sr=orig_sr, target_sr=16000)
+    return y_resampled
+
+def transcribe(audio):
+    sr,y = audio
+    y = y.astype(np.float32)
+    y/= np.max(np.abs(y))
+    y_resampled = resample_to_16k(y,sr)
+    
+    trans = pipe2(y_resampled)
+    
+    return trans["text"]
+
+demo = gr.Interface(
+            transcribe,
+            inputs="microphone",
+            outputs="text",
+            examples=["./Samples/Hindi_1.mp3","./Samples/Hindi_2.mp3","./Samples/Hindi_3.mp3","./Samples/Hindi_4.mp3","./Samples/Hindi_5.mp3"])
+demo.launch()