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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, 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
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
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}")
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