Generating a podcast using AI

Transforming a Podcast Script into a Narrated Podcast Using Python

Creating a narrated podcast from a script used to be a labor-intensive task, but with advancements in AI, the process can now be streamlined. This guide will teach you how to transform a podcast script into a narrated podcast using Python, leveraging tools like `ftfy`, `OpenAI`, and `MoviePy`.

Here is a link to a podcast that I created: Podcast

Step 1: Install Required Packages

First, you'll need to install some Python packages that will help us throughout this project. Open your terminal or command prompt and execute the following commands:

shell:

pip install ftfy
pip install openai
pip install moviepy

These commands will install:

• `ftfy`: A library to fix messy Unicode text, useful if your script contains text needing cleanup.

• `openai`: The official OpenAI client library.

• `moviepy`: A versatile package for video and audio editing.

Step 2: PrepareYour Script and Environment

Begin by importing the necessary libraries and initializing the OpenAI client. Replace `your api key` with your actual OpenAI API key.

The script itself can be generated using Open AI

The important part here is to ensure the that the script has the following format

Introduction
<CONTENT>

**Host**

Heading 1

<CONTENT>

**Host**

Heading 2

<CONTENT>

This is very important since the **Host** will be used as a delimiter to split the long text into multiple chunks

python

from ftfy import fix_text
from pathlib import Path
from openai import OpenAI
import os
from moviepy.editor import AudioFileClip, concatenate_audioclips

# Initialize OpenAI client
client = OpenAI(api_key="your api key")
data = """ insert the podcast script here """

Step 3: Clean and Chunk the Script

Clean up the script using `ftfy` and then chunk it into manageable pieces for narration.

The chunking is done so that we don’t exceed the character limit for each text in open AI

python

# Fix double-encoded sequences using ftfy
cleaned_data = fix_text(data)

# Split the text using 'Host' as the delimiter
chunks = cleaned_data.split('**Host:**')

# Create a list to hold the chunked data
chunked_data = []

for chunk in chunks:
    # Strip leading/trailing whitespace and add only non-empty chunks
    cleaned_chunk = chunk.strip()
    if cleaned_chunk:
        chunked_data.append(cleaned_chunk)

Step 4: Generate Narration Using OpenAI

Create a directory to save the audio files and use OpenAI to generate the narration for each text chunk.

python

# Define the directory to save audio files
audio_dir = Path(os.getcwd()) / "audio_chunks"

audio_dir.mkdir(exist_ok=True)

# List to store paths of audio files

audio_files = []

# Generate audio for each text chunk

for index, text in enumerate(chunked_data):

    audio_file_path = audio_dir / f"chunk_{index}.mp3"

    print(f"Generating narration for: {text}")

    # Generate audio using OpenAI's speech model

    response = client.audio.speech.create(

        model="tts-1-hd",  # Ensure the correct model name

        voice="onyx",  

        input=text

    )

    # Save generated audio to a file

    with open(audio_file_path, "wb") as f:

        f.write(response.content)

    audio_files.append(audio_file_path)

Step 5: Combine Audio Files

After generating all the audio chunks, we need to combine them into one cohesive file using MoviePy.

python

# Stitch audio files together
audio_clips = [AudioFileClip(str(file)) for file in audio_files]

combined_audio = concatenate_audioclips(audio_clips)

output_file = "combined.mp3"

combined_audio.write_audiofile(output_file, codec="libmp3lame")

print(f"Combined MP3 file saved as {output_file}")

Link to the full code : Jupiter

Conclusion

You've successfully transformed a podcast script into a narrated podcast using Python! You’ve learned how to:

1. Install and set up necessary Python packages.

2. Clean and chunk your podcast script.

3. Generate narration using OpenAI’s text-to-speech capabilities.

4. Combine individual audio files into a final podcast episode.

Feel free to experiment with different voices or add background music to further enhance your podcast. Happy podcasting!