"I want to quickly find out what's on YouTube." "I don't have time to watch a long video in its entirety."
Do you have such concerns?
In fact, if you use Python,An AI tool that automatically converts audio from YouTube videos into text and summarizes the contentYou can create it.
The process from voice recognition, text conversion, and summarization can be automated.
In this article,Explains how to create an AI that can extract only the main points from a video in a way that even beginners can understandI will.
It's perfect for those who want to save time and quickly get the information they need.
What is YouTube Summarization AI and how does it work?
conclusion
YouTube video summaries are a system that converts audio into text and then uses natural language processing to summarize the text.is.
You can bulk process this in Python.
reason
Information that would take several minutes or even several tens of minutes to convey to the human ear can be understood in just a few lines if you extract only the main points.
For voice to text conversion, use a voice recognition API (e.g. Whisper or Google Speech-to-Text),
For summarization, we use natural language processing models (e.g. GPT and T5).
Examples
• Speech recognition: Transcribing mp3 using Whisper from OpenAI
• Summarization: Compressing content using a summary model (e.g., "summarizing the main points in bullet points")
Summary
• Voice to text：Use Whisper etc.
• Summarization: Utilizing GPT-based models etc.
• Batch processing possible with Python
How to convert speech to text with Whisper
conclusion
Whisper is a highly accurate voice recognition AI that can be easily used from Python.
reason
Whisper is a speech recognition tool provided by OpenAI that accurately transcribes spoken words into text.
The API is also well-established, and it can be run by writing just a few lines of code in Python.
Code example
1 | import whisper model = whisper.load_model("base") result = model.transcribe("sample_audio.mp3") print(result["text"]) |
Summary
• WhisperSpeech recognition AI that can be used with Python
• Extract only the audio from the video and convert it to text
• Japanese also available
Use natural language processing AI for summarization
conclusion
Natural language processing models such as ChatGPT and T5 can be used for summarization.
reason
Transcribed data can be lengthy and difficult to read.
Therefore,By using summary AI to extract the main points, you can understand the content in a short amount of time.
Code example (example using OpenAI API)
1 | import openai openai.api_key = "your-api-key" response = openai.ChatCompletion.create( model="gpt-4", messages=[ {"role": "system", "content": "Please briefly summarize the following text."}, {"role": "user", "content": result["text"]} ] ) print(response["choices"][0]["message"]["content"]) |
Summary
• GPT etc.Natural language processing models are effective
• Long textSummarizing the transcription results
• Cost depends on the API, but there is a free tier
Steps to extract audio from YouTube videos
conclusion
Converting it into an audio file makes it easier to transcribe.
reason
YouTube videos are in mp4 format, so audio cannot be extracted as is.
Therefore,Convert to audio only (mp3) using ffmpeg etc.I will.
Example command
1 | ffmpeg -i sample_video.mp4 -ab 160k -ac 2 -ar 44100 -vn output_audio.mp3 |
Summary
• mp4 to mp3 conversionRequires ffmpeg
• After conversion, you can transcribe it with Whisper
• Commands can be written in one line
Flow of automating the whole process using Python
conclusion
Automation is possible by processing the entire process in bulk using Python.
reason
Using multiple tools manually can be tedious.
Python can extract, convert, and summarize audioBulk processing scriptsYou can create it.
Configuration image
• Convert mp4 to mp3 (ffmpeg)
• mp3 to text (Whisper)
• Text → Summary (ChatGPT API)
Summary
• It's all wrapped up in a Python script.
• One click awaySummarization AI is complete
• Saves time
Precautions and supplements for use
conclusion
You must be mindful of API restrictions and copyrights.
reason
YouTube content is copyrighted.Be careful with any automated processing of content.
In addition, there is a limit to the number of times the API can be used for free, so large-volume processing will incur costs.
Summary of points to note
• Commercial use may not be permitted
• The accuracy of summaries is limited
• Free API has limitations
summary
Using Python,AI that transcribes YouTube audio and automatically summarizes the main pointsAnyone can create it.
• Whisper transcription
• Summarized with ChatGPT API
• Extract audio with ffmpeg
Just by remembering this flow, you will be free from having to watch long periods of videos.
This is a recommended skill for those who want to save time and get only the information they need.
English 
Japanese