Update app.py

app.py

@@ -2,19 +2,28 @@ import gradio as gr
 from transformers import pipeline
 import numpy as np
 
-transcriber = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec-hindi")
+transcriber_hindi = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec-hindi")
+transcriber_bang = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_bengali")
+transcriber_odia = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec-odia")
 
-def transcribe(audio):
+
+def transcribe(audio,lang = "hindi"):
+    
+        
     sr, y = audio
     y = y.astype(np.float32)
     y /= np.max(np.abs(y))
-
-    return transcriber({"sampling_rate": sr, "raw": y})["text"]
+    if lang  == "hindi":
+        return transcriber_hindi({"sampling_rate": sr, "raw": y})["text"]
+    if lang  == "bangali":
+        return transcriber_bang({"sampling_rate": sr, "raw": y})["text"]
+    if lang  == "odia":
+        return transcriber_odia({"sampling_rate": sr, "raw": y})["text"]    
 
 
 demo = gr.Interface(
     transcribe,
-    gr.Audio(source="microphone"),
+    [gr.Audio(source="microphone"),gr.radio(["hindi","bangali","odia"])
     "text",
 )