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Update app.py
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app.py
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import streamlit as st
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import
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from transformers import pipeline
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st.title("
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# Choose the translation models from Hugging Face
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translation_models = {
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"French to English": "Helsinki-NLP/opus-mt-fr-en",
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"English to Urdu": "Helsinki-NLP/opus-mt-en-ur",
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"Urdu to English": "Helsinki-NLP/opus-mt-ur-en",
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"English to Spanish": "Helsinki-NLP/opus-mt-en-es",
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"Spanish to English": "Helsinki-NLP/opus-mt-es-en",
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"English to Chinese": "Helsinki-NLP/opus-mt-en-zh",
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"Chinese to English": "Helsinki-NLP/opus-mt-zh-en",
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# Add more language pairs as needed
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}
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# Load the translation pipeline
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translator = pipeline(task="translation", model=translation_models[selected_translation])
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#
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st.
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"This is an enhanced Multilingual Translator chatbot that uses the Hugging Face Transformers library."
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)
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st.write(
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"Select a translation model from the dropdown, enter text, and click 'Translate' to see the translation."
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import streamlit as st
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import speech_recognition as sr
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from transformers import pipeline
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st.title("Speech-to-Text and Translation Chatbot")
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# Choose the translation models from Hugging Face
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translation_models = {
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"French to English": "Helsinki-NLP/opus-mt-fr-en",
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"English to Urdu": "Helsinki-NLP/opus-mt-en-ur",
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"Urdu to English": "Helsinki-NLP/opus-mt-ur-en",
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# Add more language pairs as needed
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}
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# Load the translation pipeline
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translator = pipeline(task="translation", model=translation_models[selected_translation])
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# Function to perform speech-to-text and translation
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def speech_to_text_and_translate():
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recognizer = sr.Recognizer()
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st.info("Speak into your microphone...")
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with sr.Microphone() as source:
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audio_data = recognizer.listen(source, timeout=10)
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try:
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text = recognizer.recognize_google(audio_data)
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st.success(f"Speech-to-Text Result: {text}")
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# Perform translation
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translated_text = translator(text, max_length=500)[0]['translation_text']
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st.success(f"Translated Text: {translated_text}")
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except sr.UnknownValueError:
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st.warning("Speech recognition could not understand audio.")
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except sr.RequestError as e:
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st.error(f"Error with the speech recognition service: {e}")
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# Use speech-to-text and translation
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if st.button("Start Speech-to-Text and Translation"):
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speech_to_text_and_translate()
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