Update app.py

app.py

@@ -16,8 +16,9 @@ transcriber_telugu = pipeline("automatic-speech-recognition", model="krishnateja
 transcriber_tamil = pipeline("automatic-speech-recognition", model="Amrrs/wav2vec2-large-xlsr-53-tamil")
 # transcriber_nepali = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_nepali")
 # transcriber_marathi = pipeline("automatic-speech-recognition", model="ai4bharat/indicwav2vec_v1_marathi")
+transcriber_kannada = pipeline("automatic-speech-recognition", model="TheAIchemist13/kannada_wav2vec2_final")
 
-languages = ["hindi","bengali","odia","gujarati","telugu","tamil"]
+languages = ["hindi","bengali","odia","gujarati","telugu","tamil","kannada"]
 
 def resample_to_16k(audio, orig_sr):
     y_resampled = librosa.resample(y=audio, orig_sr=orig_sr, target_sr=16000)
@@ -39,7 +40,7 @@ def transcribe(audio,lang="hindi"):
 
 demo = gr.Interface(
             transcribe,
-            inputs=["microphone",gr.Radio(["hindi","bengali","odia","gujarati","telugu","tamil"],value="hindi")],
+            inputs=["microphone",gr.Radio(["hindi","bengali","odia","gujarati","telugu","tamil","kannada"],value="hindi")],
             # inputs=["microphone",gr.Radio(["hindi","bengali","odia","gujarati","telugu","sinhala","tamil","nepali","marathi"],value="hindi")],
             outputs=["text","text"],
             examples=[["./Samples/Hindi_1.mp3","hindi"],["./Samples/Hindi_2.mp3","hindi"],["./Samples/Hindi_3.mp3","hindi"],["./Samples/Hindi_4.mp3","hindi"],["./Samples/Hindi_5.mp3","hindi"],["./Samples/Tamil_2.mp3","hindi"],["./Samples/climate ex short.wav","hindi"],["./Samples/Gujarati_1.wav","gujarati"],["./Samples/Gujarati_2.wav","gujarati"],["./Samples/Bengali_1.wav","bengali"],["./Samples/Bengali_2.wav","bengali"]])