Project overview
In this project, you’ll assume the role of a Python developer tasked with building a speech recognition and summarization system. Using the vosk library for speech-to-text and Hugging Face models for summarization, you’ll develop a system to automatically transcribe audio files like lecture notes, podcasts, or videos and generate concise summaries.
Throughout the project, you’ll apply Python programming skills and leverage pre-trained models to convert speech to text, add punctuation, handle long audio files, and extract key points into a summary. This real-world project will enhance your portfolio, demonstrating your ability to combine speech recognition and natural language processing techniques for practical applications.
Objective: Build a speech recognition and summarization system to automatically transcribe and summarize audio files, showcasing your Python skills in a real-world context.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Installing and importing Python packages for speech recognition and text summarization
- Working with Python data types, variables, and functions
- Implementing control flow statements like loops and conditionals in Python
- Manipulating and analyzing data using Python libraries like NumPy and pandas
Projects steps
Step 1: Project Overview
Step 2: Speech Recognition: Downloading the Model and Audio Files
Step 3: Speech Recognition: Initializing a Recognizer
Step 4: Speech Recognition: Loading an Audio File
Step 5: Speech Recognition: Transcribing the Audio File into Text
Step 6: Adding Punctuation to the Transcript
Step 7: Defining A Function to Transcribe Longer Audio Files
Step 8: Summarizing the Transcripts
Step 9: Wrapping Up
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