Init repo

app.py

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+from gtts import gTTS
+from transformers import pipeline
+import gradio as gr
+import uuid
+
+asr = pipeline('automatic-speech-recognition', "facebook/wav2vec2-conformer-rope-large-960h-ft")
+corrector = pipeline("text2text-generation", model="pszemraj/grammar-synthesis-small")
+
+transcribe = lambda audio: asr(audio)['text'].lower()
+
+def to_audio(s):
+  audio_path = f'/tmp/{uuid.uuid4()}.mp3'
+  tts = gTTS(s, tld='us')
+  tts.save(audio_path)
+  return audio_path
+
+
+#@title English Learning
+def transcription(audio, history):
+  if audio:
+    message = transcribe(audio)
+    history.append(( (audio, ) , message))
+    results = corrector(message)
+    results = '\n'.join([t['generated_text'] for t in results])
+    history.append( (None, f'**[Grammar and examples]**\n {results}') )
+
+  return history
+
+def chat(message, history):
+  audio_path = to_audio(message)
+  history.append((message, (audio_path,)))
+  results = corrector(message)
+  results = '\n'.join([t['generated_text'] for t in results])
+  history.append( (None, f'**[Grammar and examples]**\n {results}') )
+  
+  return None, history
+
+with gr.Blocks(theme=gr.themes.Soft()) as learning:
+    gr.Markdown('# The main aim of this app is to help English learners to speak fluently.')
+
+    chatbot = gr.Chatbot()
+
+    with gr.Row():
+      message = gr.Textbox(label='Send your message to TTS')
+      microphone = gr.Audio(label="Transcribe", source="microphone", type="filepath")
+    
+    microphone.change(transcription, [microphone, chatbot], [chatbot])
+    microphone.change(lambda:None, None, microphone)
+    message.submit(chat, [message, chatbot], [message, chatbot])
+
+learning.launch()

requirements.txt

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+gtts
+transformers
+gradio