Create app.py

app.py

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+#Importing all the necessary packages
+import nltk
+import librosa
+import torch
+import gradio as gr
+from transformers import Wav2Vec2Tokenizer, Wav2Vec2ForCTC
+nltk.download("punkt")
+  
+  
+
+def correct_casing(input_sentence):
+  """ This function is for correcting the casing of the generated transcribed text
+  """
+  sentences = nltk.sent_tokenize(input_sentence)
+  return (' '.join([s.replace(s[0],s[0].capitalize(),1) for s in sentences]))
+  
+
+
+def asr_transcript(audio_file, language):
+    """Generating transcripts for the audio input
+    """
+    
+    #Selecting the language and loading the model and the tokenizer
+    if language == "English":
+        model_name = "facebook/wav2vec2-large-960h-lv60-self"
+    elif language == "Russian":
+        model_name = "jonatasgrosman/wav2vec2-large-xlsr-53-russian"
+    
+    tokenizer = Wav2Vec2Tokenizer.from_pretrained(model)
+    model = Wav2Vec2ForCTC.from_pretrained(model)
+  
+    #read the file and resample to 16KHz
+    stream = librosa.stream(audio_file.name, block_length=20, frame_length=16000, hop_length=16000)
+
+    for speech in stream:
+        if len(speech.shape) > 1:
+            speech = speech[:, 0] + speech[:, 1]
+
+        input_values = tokenizer(speech, return_tensors="pt").input_values
+        logits = model(input_values).logits
+
+        predicted_ids = torch.argmax(logits, dim=-1)
+        transcription = tokenizer.batch_decode(predicted_ids)[0]
+        transcript += transcription.lower() + " "
+
+    return transcript
+  
+
+gr.Interface(asr_transcript,
+             inputs = [gr.inputs.Audio(source="microphone", type="filepath", optional=True, label="Please record your message/Пожалуйста, введите Ваше сообщение"), 
+             gr.inputs.Radio(label="Pick a language/Выберите язык", choices=["English", "Russian"])
+             outputs = gr.outputs.Textbox(label="Output Text/Результат"),
+             title="Automatic speech recognition with voice recorder in Russian and English",
+             description = "This application displays transcribed text for given audio input",
+             theme="grass").launch()