Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 import gradio as gr
 import sox
 import subprocess
-
+from fuzzywuzzy import fuzz
 
 def read_file_and_process(wav_file):
     filename = wav_file.split('.')[0]
@@ -36,10 +36,12 @@ def parse(wav_file):
         logits = model(**input_values).logits
     return parse_transcription(logits)
 
-model_id = "facebook/wav2vec2-base-100h"
+
+model_id = "jonatasgrosman/wav2vec2-large-xlsr-53-persian"
 processor = Wav2Vec2Processor.from_pretrained(model_id)
 model = Wav2Vec2ForCTC.from_pretrained(model_id)
 
+
 input_ = gr.Audio(source="microphone", type="filepath")
 txtbox = gr.Textbox(
             label="persian text output:",
@@ -53,12 +55,11 @@ txtbox = gr.Textbox(
 
 title = "Speech-to-Text (persian)"
 description = "Upload a prsian audio, and let AI do the hard work of transcribing."
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2104.06678'>Large-Scale Self- and Semi-Supervised Learning for Speech Translation</a></p>"
+article = "<p style='text-align: center'><a href='https://github.com/nimaprgrmr'>Large-Scale Self- and Semi-Supervised Learning for Speech Translation</a></p>"
+
 
 
-while output != "خروج":
-    demo = gr.Interface(fn=parse, inputs = input_,  outputs=txtbox, title=title, description=description, article = article,
-                 streaming=True, interactive=True,
-                 analytics_enabled=False, show_tips=False, enable_queue=True)
-    demo.launch(share=True)
-    output = outpts
+demo = gr.Interface(fn=parse, inputs = input_,  outputs=txtbox, title=title, description=description, article = article,
+             streaming=True, interactive=True,
+             analytics_enabled=False, show_tips=False, enable_queue=True)
+demo.launch(share=True)