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import streamlit as st | |
from transformers import pipeline | |
from gtts import gTTS | |
import speech_recognition as sr | |
import sounddevice as sd # Import sounddevice | |
# Create a translation pipeline | |
pipe = pipeline('translation', model='Helsinki-NLP/opus-mt-en-hi') | |
# Initialize the SpeechRecognition recognizer | |
recognizer = sr.Recognizer() | |
# Create a Streamlit input element for microphone input | |
audio_input = st.empty() | |
# Check if the microphone input is requested | |
if st.checkbox("Use Microphone for English Input"): | |
with audio_input: | |
st.warning("Listening for audio input... Speak in English.") | |
try: | |
# Replace pyaudio.Microphone with sd.InputStream | |
with sd.InputStream(callback=None, channels=1, dtype='int16', samplerate=16000): | |
with sr.AudioFile("temp.wav") as source: # Save audio to temp.wav | |
recognizer.adjust_for_ambient_noise(source) | |
audio = recognizer.listen(source) | |
st.success("Audio input recorded. Translating...") | |
# Recognize the English speech | |
english_text = recognizer.recognize_google(audio, language='en') | |
# Translate the English text to Hindi | |
out = pipe(english_text, src_lang='en', tgt_lang='hi') | |
# Extract the translation | |
translation_text = out[0]['translation_text'] | |
st.text(f"English Input: {english_text}") | |
st.text(f"Hindi Translation: {translation_text}") | |
# Convert the translated text to speech | |
tts = gTTS(translation_text, lang='hi') | |
tts.save("translated_audio.mp3") | |
# Display the audio player for listening to the speech | |
st.audio("translated_audio.mp3", format='audio/mp3') | |
except sr.WaitTimeoutError: | |
st.warning("No speech detected. Please speak into the microphone.") | |
except sr.RequestError as e: | |
st.error(f"Could not request results from Google Speech Recognition service: {e}") | |
except sr.UnknownValueError: | |
st.warning("Speech recognition could not understand the audio.") | |