use conformer ctc large

app.py

@@ -27,7 +27,7 @@ def asr_transcript(audio):
     data={}
     if audio:
         text_asr = asr_model.transcribe_file(audio.name) 
-        text_nemo_trasducer = transcribe(audio, "stt_rw_conformer_transducer_large")
+        text_nemo_trasducer = transcribe(audio, "stt_rw_conformer_ctc_large")
         with open(audio.name,'rb') as f:
             audio_proper = f.read()
         stt_engine = SpeechToTextEngine()
@@ -53,7 +53,7 @@ gradio_ui = gr.Interface(
     inputs=[ gr.inputs.Audio(source="microphone", type="file", optional=True, label="Record from microphone")],
     outputs=[gr.outputs.Textbox(label="Recognized speech from speechbrain model"),
              gr.outputs.Textbox(label="Recognized speech from coqui STT model"),
-             gr.outputs.Textbox(label="Recognized speech from NVIDIA Conformer transduver large model")]
+             gr.outputs.Textbox(label="Recognized speech from NVIDIA conformer ctc large model")]
     # examples =  [["sample_1.wav"],["sample_2.wav"]]
 )