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import streamlit as st
from transformers import pipeline
from gtts import gTTS
import speech_recognition as sr
import pyaudio
# Create a translation pipeline
pipe = pipeline('translation', model='Helsinki-NLP/opus-mt-en-hi')
# Initialize the SpeechRecognition recognizer
recognizer = sr.Recognizer()
# Find the microphone device index
def find_microphone_index():
p = pyaudio.PyAudio()
for i in range(p.get_device_count()):
device_info = p.get_device_info_by_index(i)
if "microphone" in device_info["name"].lower():
return i
return None
# Get the microphone device index
microphone_index = find_microphone_index()
audio_input = st.empty()
# Check if the microphone input is requested
if st.checkbox("Use Microphone for English Input"):
with audio_input:
if microphone_index is None:
st.warning("No microphone found. Please make sure your microphone is connected.")
else:
st.warning("Listening for audio input... Speak in English.")
try:
with sr.Microphone(device_index=microphone_index) as 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.")
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