OCR-Translator / translate_speak.py
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from gtts import gTTS
from deep_translator import GoogleTranslator
import soundfile as sf
import tempfile
import numpy as np
import gtts
output_path = 'Audio/output.wav'
translate_path = 'Audio/translate.wav'
def get_lang(lang):
translate = GoogleTranslator().get_supported_languages()
speak = list(gtts.lang.tts_langs().values())
speak = list(map(lambda x: x.lower(), speak))
speak.sort()
set_lang = list(set(speak) & set(translate))
set_lang.sort()
if lang in set_lang:
for key, value in gtts.lang.tts_langs().items():
if value.lower() == lang:
return key
else:
return 'en'
else:
return 'en'
def audio_streaming(txt=None, lang='en', to=None):
# If an audio file is provided as input, use it; otherwise, use the direct file path
speak = gTTS(text=txt, lang=lang, slow=False)
if to == 1:
audio = output_path
else:
audio = translate_path
speak.save(audio)
# Load the audio file
data, samplerate = sf.read(audio)
# Ensure data is in float32 format
data = np.array(data, dtype=np.float32)
# Save to a temporary file that Gradio can use for audio playback
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
sf.write(tmp_file.name, data, samplerate)
temp_audio_path = tmp_file.name
# Return the file path to Gradio
return temp_audio_path
def translate_txt(lang, text):
translator = GoogleTranslator(source="en", target=lang)
translated_text = translator.translate(text)
audio_path = audio_streaming(translated_text, lang=get_lang(lang), to=2)
return translated_text, audio_path
if __name__ == "__main__":
# print(audio_streaming("hello world"))
# os.system(f"start {audio_streaming('hello world!')}")
translate = GoogleTranslator().get_supported_languages()
# print(f"Can translate: {translate}", len(translate))
# print()
speak = list(gtts.lang.tts_langs().values())
speak = list(map(lambda x: x.lower(), speak))
speak.sort()
# print(f"Can speak: {speak}", len(speak))
# print()
set_lang = list(set(speak)&set(translate))
set_lang.sort()
# print(f"Set of lang: {set_lang}", len(set_lang))
not_in_speak = list(set(translate) - set(speak))
print(not_in_speak)