VTT Translation Project

This project provides a set of scripts to process, translate, and merge VTT (Web Video Text Tracks) files. The main steps include extracting specific lines from a VTT file, translating those lines using the Google Translate API, and merging the translations back into the original VTT file.

Table of Contents

• VTT Translation Project
  • Table of Contents
  • Prerequisites
  • Installation
  • Usage
    • Step 1: Add your non EN file to src/files/transcript

Prerequisites

• Python 3.x
• Google Cloud Translate API credentials
• Required Python libraries: python-docx, google-cloud-translate

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/vtt-translation-project.git
   cd vtt-translation-project

2. Install the required Python libraries:

   ./bootstrap.sh

3. Set up Google Cloud Translate API credentials:

   • Follow the instructions here to set up your Google Cloud project and obtain the credentials JSON file.
   • Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of your credentials JSON file:

     export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your/credentials.json"

Usage

Step 1: Add your non EN file to src/files/transcript

After run main.py dist file will be generated with the following files:

• Modified_transcript.vtt

  • All the unnessery lines will be skipped and keep the acuall transaction lines and will be saved to transcript.docx

    WEBVTT
    
    1
    00:00:00.030 --> 00:00:01.180
    Name: Ja.
    
    2
    00:00:11.780 --> 00:00:12.830
    Name: Eine.
    
    3
    00:00:14.510 --> 00:00:28.789
    Name: Hier fehlt ein kleines Wort. Das ist kein Artikel. Das ist ein Wort, das wir verwenden, wenn wir Zusätze haben mit der Frage, wofür?
    
    4
    00:00:29.140 --> 00:00:30.470
    Name: Wofür?
    
    5
    00:00:32.259 --> 00:00:32.599
    Name: Um.
    
    6
    00:00:34.730 --> 00:00:35.370
    Name: Oma.
    
    7
    00:00:35.370 --> 00:00:38.160
    Name: Wofür benutzen wir eine Waschmaschine?
    
    8
    00:00:38.670 --> 00:00:48.030
    Name: Wir benutzen sie, um schmutzige Kleidung wieder sauber zu machen. Dieser Satz mit um. Der hat kein Subjekt.
    

• transcript.docx

  • WIll include the dialog scriopts only, then this file will be translated to the English language using Google translate API and save the oyput to en-transcript.docx

• DE_EN_transcript.vtt

  • Will contain the the transscript with teh non english language then the English script will be added below.

    WEBVTT
    
    1
    00:00:00.030 --> 00:00:01.180
    Name: Ja.
    Name: Yes.
    
    2
    00:00:11.780 --> 00:00:12.830
    Name: Eine.
    Name: One.
    
    3
    00:00:14.510 --> 00:00:28.789
    Name: Hier fehlt ein kleines Wort. Das ist kein Artikel. Das ist ein Wort, das wir verwenden, wenn wir Zusätze haben mit der Frage, wofür?
    Name: There is a small word missing here. It is not an article. It is a word we use when we have additions with the question, what for?
    
    4
    00:00:29.140 --> 00:00:30.470
    Name: Wofür?
    Name: For what?
    
    5
    00:00:32.259 --> 00:00:32.599
    Name: Um.
    Name: Um.
    
    6
    00:00:34.730 --> 00:00:35.370
    Name: Oma.
    Name: My own.
    
    7
    00:00:35.370 --> 00:00:38.160
    Name: Wofür benutzen wir eine Waschmaschine?
    Name: What do we use a washing machine for?
    
    8
    00:00:38.670 --> 00:00:48.030
    Name: Wir benutzen sie, um schmutzige Kleidung wieder sauber zu machen. Dieser Satz mit um. Der hat kein Subjekt.
    Name: We use them to clean dirty clothes again. This sentence with um. It has no subject.