!pip install yt-dlp ffmpeg-python faster-whisper gradio transformers !apt-get install ffmpeg -y # Importing required libraries import os import yt_dlp import ffmpeg import gradio as gr from faster_whisper import WhisperModel from transformers import

1. Introduction 1.1 Background and Motivation 1.2 Objectives and Scope 1.3 Methodology Overview 1.4 Structure of the Thesis 2. Overview of Required Libraries 2.1 yt-dlp 2.2 ffmpeg-python 2.3 faster-whisper 2.4 gradio 2.5 transformers 3. Installation Process 3.1 Installing yt-dlp and ffmpeg 3.2 Installing faster-whisper Library 3.3 Installing gradio and transformers 3.4 Troubleshooting Installation Issues 4. Practical Applications 4.1 Audio/Video Download and Processing 4.2 Speech Recognition with WhisperModel 4.3 Building Interfaces with Gradio 4.4 Natural Language Processing with Transformers 5. Methodology 5.1 Data Collection Process 5.2 Pipeline Development 5.3 Evaluation Metrics 5.4 Case Study Selection 6. Case Studies 6.1 Case Study One: Application Setup 6.2 Case Study Two: Performance Analysis 6.3 Case Study Three: User Interaction 6.4 Comparative Analysis 7. Results and Discussion 7.1 Analysis of Application Results 7.2 Interpretation of Findings 7.3 Limitations of the Study 7.4 Implications for Future Work 8. Conclusion 8.1 Summary of Findings 8.2 Contributions to the Field 8.3 Recommendations for Practitioners 8.4 Final Thoughts