Update app.py

app.py

@@ -8,7 +8,7 @@ transcriber_hindi = pipeline("automatic-speech-recognition", model="ai4bharat/in
 transcriber_bengali = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_bengali")
 transcriber_odia = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec-odia")
 transcriber_gujarati = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_gujarati")
-transcriber_telugu = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_telugu")
+# transcriber_telugu = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_telugu")
 transcriber_sinhala = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_sinhala")
 transcriber_tamil = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_tamil")
 transcriber_nepali = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_nepali")
@@ -19,16 +19,19 @@ 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):
+def transcribe(audio,lang="hindi"):
     sr,y = audio
     y = y.astype(np.float32)
     y/= np.max(np.abs(y))
     y_resampled = resample_to_16k(y,sr)
-
+    if lang=="telugu":
+        return "No Model","So no time!"
     pipe= eval(f'transcriber_{lang}')
+    start_time = time.time()
     trans = pipe(y_resampled)
+    end_time = time.time()
     
-    return trans["text"]
+    return trans["text"],(end_time-start_time)
 
 demo = gr.Interface(
             transcribe,