audio_translation / translate.py
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import os
import moviepy.editor as mp
import assemblyai as aai
import requests
import azure.cognitiveservices.speech as speechsdk
from moviepy.editor import AudioFileClip
from gradio_client import Client
class Translate:
def __init__(self, video_path,original_language, target_language):
self.video_path = video_path
self.target_language = target_language
self.original_language=original_language
self.aai_api_key = "c29eb650444a4ae4be6a787ebb15d5e2"
self.translation_api_key = "394833878dd54214886cd81a35ac35dc"
self.spechtotxt_key = "07ac642da789462d87ad47a790ec6d5f"
def extract_audio(self):
aai.settings.api_key = self.aai_api_key
video = mp.VideoFileClip(self.video_path)
audio = video.audio
audio_path = "audio.wav"
audio.write_audiofile(audio_path)
print("Audio extracted successfully!")
return audio_path
def org_language_parameters(self,original_language):
if original_language == 'English':
self.lan_code='en'
elif original_language =='German':
self.lan_code='de'
elif original_language =='French':
self.lan_code='fr'
elif original_language =='Spanish':
self.lan_code='es'
else:
self.lan_code = ''
def set_language_parameters(self, target_language):
if target_language == 'English':
self.language_code = 'en-US'
self.trans_code = 'en'
elif target_language == 'German':
self.language_code = 'de-DE'
self.trans_code = 'de'
elif target_language == 'French':
self.language_code = 'fr-CA'
self.trans_code = 'fr'
elif target_language == 'Spanish':
self.language_code = 'es-ES'
self.trans_code = 'es'
elif target_language == 'Urdu':
self.language_code = 'ur-PK'
self.trans_code = 'ur'
else:
# Handle unsupported languages or set default values
self.voice_names = []
self.language_code = ''
self.trans_code = ''
print("Target Language:", target_language)
print("Trans Code:", self.trans_code)
def get_voice_names(self):
return self.voice_names
def get_language_code(self):
return self.language_code
def transcribe_audio(self, audio_path):
aai.settings.api_key = self.aai_api_key
config = aai.TranscriptionConfig(self.lan_code)
transcriber = aai.Transcriber(config=config)
transcript = transcriber.transcribe(audio_path)
file_path = "transcript.srt"
filepath = "t.txt"
with open(file_path, "w") as file:
file.write(transcript.export_subtitles_srt())
with open(filepath, "w") as file:
file.write(transcript.text)
def translate_text(self, text):
base_url = "https://api.cognitive.microsofttranslator.com"
endpoint = "/translate"
headers = {
"Ocp-Apim-Subscription-Key": self.translation_api_key,
"Content-Type": "application/json",
"Ocp-Apim-Subscription-Region": "southeastasia"
}
params = {
"api-version": "3.0",
"to": self.trans_code
}
body = [{"text": text}]
response = requests.post(base_url + endpoint, headers=headers, params=params, json=body)
response.raise_for_status()
translation = response.json()[0]["translations"][0]["text"]
return translation
def transcribe_and_translate(self):
audio_path = self.extract_audio()
self.org_language_parameters(self.original_language)
self.transcribe_audio(audio_path)
self.set_language_parameters(self.target_language)
# Assuming t.txt contains the original text
with open("t.txt", 'r', encoding='utf-8') as text_file:
original_text = text_file.read()
self.org_language_parameters(self.original_language)
# Translate the entire original text
translated_text = self.translate_text(original_text)
# Write the translated text to a new text file
translated_text_path = "translated_text.txt"
with open(translated_text_path, 'w', encoding='utf-8') as translated_file:
translated_file.write(translated_text)
print("Translation complete. Translated text saved to:", translated_text_path)
return translated_text_path
# class Translate:
# def __init__(self, video_path, target_language,original_language,speaking_rate):
# self.video_path = video_path
# self.target_language = target_language
# self.original_language=original_language
# self.aai_api_key = "c29eb650444a4ae4be6a787ebb15d5e2"
# self.txtospech_key = "358c77527e48454cbf5bf2bd54f03161"
# self.translation_api_key = "394833878dd54214886cd81a35ac35dc"
# self.spechtotxt_key = "07ac642da789462d87ad47a790ec6d5f"
# self.speaking_rate= speaking_rate
# self.print_parameters()
# def print_parameters(self):
# print("Video_Path" , self.video_path)
# print("original_language" , self.original_language)
# print("target_language" , self.target_language)
# print("speaking_rate" , self.speaking_rate)
# def extract_audio(self):
# aai.settings.api_key = self.aai_api_key
# video = mp.VideoFileClip(self.video_path)
# audio = video.audio
# audio_path = "audio.wav"
# audio.write_audiofile(audio_path)
# print("Audio extracted successfully!")
# return audio_path
# def gender_detection(self):
# # gender_model_url = "https://salman11223-gender-detection.hf.space/--replicas/wml9f/"
# # gender_client = Client(gender_model_url)
# # gender = gender_client.predict(
# # 'audio.wav', api_name="/predict"
# # )
# # print(gender)
# # return gender
# return "male"
# def org_language_parameters(self,original_language):
# if original_language == 'English':
# self.lan_code='en'
# elif original_language =='German':
# self.lan_code='de'
# elif original_language =='French':
# self.lan_code='fr'
# elif original_language =='Spanish':
# self.lan_code='es'
# else:
# self.lan_code = ''
# def set_language_parameters(self, target_language, detected_gender):
# if target_language == 'English':
# self.language_code = 'en-US'
# self.trans_code = 'en'
# self.voice_names = 'en-US-GuyNeural' if detected_gender == 'male' else 'en-US-AriaNeural'
# elif target_language == 'German':
# self.language_code = 'de-DE'
# self.trans_code = 'de'
# self.voice_names = 'de-DE-ConradNeural' if detected_gender == 'male' else 'de-DE-KatjaNeural'
# elif target_language == 'French':
# self.language_code = 'fr-CA'
# self.trans_code = 'fr'
# self.voice_names = 'fr-CA-JeanNeural' if detected_gender == 'male' else 'fr-CA-SylvieNeural'
# elif target_language == 'Spanish':
# self.language_code = 'es-ES'
# self.trans_code = 'es'
# self.voice_names = 'es-ES-AlvaroNeural' if detected_gender == 'male' else 'es-ES-ElviraNeural'
# elif target_language == 'Urdu':
# self.language_code = 'ur-PK'
# self.trans_code = 'ur'
# self.voice_names = 'ur-PK-AsadNeural' if detected_gender == 'male' else 'ur-PK-UzmaNeural'
# else:
# # Handle unsupported languages or set default values
# self.voice_names = []
# self.language_code = ''
# self.trans_code = ''
# print("Target Language:", target_language)
# print("Trans Code:", self.trans_code)
# def get_voice_names(self):
# return self.voice_names
# def get_language_code(self):
# return self.language_code
# def get_audio_duration(self, audio_path):
# audio_clip = AudioFileClip(audio_path)
# audio_duration = audio_clip.duration
# return audio_duration
# def transcribe_audio(self, audio_path):
# aai.settings.api_key = self.aai_api_key
# config = aai.TranscriptionConfig(self.lan_code)
# transcriber = aai.Transcriber(config=config)
# transcript = transcriber.transcribe(audio_path)
# file_path = "transcript.srt"
# filepath = "t.txt"
# with open(file_path, "w") as file:
# file.write(transcript.export_subtitles_srt())
# with open(filepath, "w") as file:
# file.write(transcript.text)
# def generate_ssml(self, text, speaking_rate):
# # Construct SSML with the given text, speaking rate, voice name, and language code
# return f'<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis" xml:lang="{self.language_code}"><voice name="{self.voice_names}"><prosody rate="{speaking_rate}">{text}</prosody></voice></speak>'
# def text_to_speech(self, text, apikey, reggion, out_aud_file, speaking_rate):
# ssml = self.generate_ssml(text, speaking_rate)
# speech_config = speechsdk.SpeechConfig(subscription=apikey, region=reggion)
# audio_config = speechsdk.audio.AudioOutputConfig(filename=out_aud_file)
# speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
# speech_synthesizer.speak_ssml_async(ssml).get()
# def translate_text(self, text):
# base_url = "https://api.cognitive.microsofttranslator.com"
# endpoint = "/translate"
# headers = {
# "Ocp-Apim-Subscription-Key": self.translation_api_key,
# "Content-Type": "application/json",
# "Ocp-Apim-Subscription-Region": "southeastasia"
# }
# params = {
# "api-version": "3.0",
# "to": self.trans_code
# }
# body = [{"text": text}]
# response = requests.post(base_url + endpoint, headers=headers, params=params, json=body)
# response.raise_for_status()
# translation = response.json()[0]["translations"][0]["text"]
# return translation
# def transcribe_and_translate(self):
# audio_path = self.extract_audio()
# self.org_language_parameters(self.original_language)
# self.transcribe_audio(audio_path)
# gender = self.gender_detection()
# print("Detected Gender:", gender)
# self.set_language_parameters(self.target_language,gender)
# with open("transcript.srt", 'r') as srt_file:
# original_srt_content = srt_file.read()
# original_subtitles = original_srt_content.strip().split('\n\n')
# translated_subtitles = []
# for subtitle in original_subtitles:
# lines = subtitle.split('\n')
# sequence_number = lines[0]
# timestamp = lines[1]
# original_text = '\n'.join(lines[2:])
# translated_text = self.translate_text(original_text)
# translated_subtitle = f"{sequence_number}\n{timestamp}\n{translated_text}"
# translated_subtitles.append(translated_subtitle)
# translated_srt_content = '\n\n'.join(translated_subtitles)
# translated_srt_path = "translated_file.srt"
# with open(translated_srt_path, 'w', encoding='utf-8') as srt_file:
# srt_file.write(translated_srt_content)
# # Loop through each translated subtitle and generate speech
# translated_audio_paths = []
# for subtitle in translated_subtitles:
# lines = subtitle.split('\n')
# sequence_number = lines[0]
# timestamp = lines[1]
# translated_text = '\n'.join(lines[2:])
# translated_audio_path = f"translated_audio_{sequence_number}.wav"
# self.text_to_speech(translated_text, self.txtospech_key, "southeastasia", translated_audio_path, self.speaking_rate)
# translated_audio_paths.append(translated_audio_path)
# # Create a list to store the audio clips
# translated_audio_clips = []
# # Loop through each translated audio path and create an AudioFileClip
# for audio_path in translated_audio_paths:
# translated_audio_clip = mp.AudioFileClip(audio_path)
# translated_audio_clips.append(translated_audio_clip)
# # Concatenate the translated audio clips into a single audio file
# translated_audio = mp.concatenate_audioclips(translated_audio_clips)
# # Define the output audio file path
# output_audio_path = "translated_audio.wav"
# # Write the concatenated translated audio to the output file
# translated_audio.write_audiofile(output_audio_path)
# # Load the original video
# video = mp.VideoFileClip(self.video_path)
# # Load the translated audio
# translated_audio = mp.AudioFileClip(output_audio_path)
# # Set the audio of the video to the translated audio
# video = video.set_audio(translated_audio)
# # Define the output video file path
# output_video_path = "translated_video.mp4"
# # Write the video with translated audio to the output file
# video.write_videofile(output_video_path, codec="libx264", audio_codec="aac")
# # Clean up temporary files
# self.cleanup_temp_files()
# def cleanup_temp_files(self):
# temp_files = ["audio.wav", "t.txt", "transcript.srt","translated_audio.wav","translated_file.srt"] + [f"translated_audio_{i}.wav" for i in range(1, 100)] # Adjust the range accordingly
# for file in temp_files:
# if os.path.exists(file):
# os.remove(file)
# print(f"Deleted {file}")