tts-joinery 1.0.5

Automate chunking long texts to produce a single audio file from text-to-speech APIs

tts-joinery

tts-joinery is a Python library and CLI tool to work around length limitations in text-to-speech APIs.

Since currently-popular APIs are limited to 4096 characters, this library will:

• Chunk the input text into sentences using the NLTK Punkt module (for better audio by avoiding segments split in the middle of a word or sentence).
• Run each chunk through the TTS API
• Join together the resulting output to produce a single MP3 file

Currently only the OpenAI API is supported, with the intent to add more in the future.

Installation

pip install tts-joinery

or use pipx to install as a standalone tool.

Requires ffmpeg for the audio file processing.

Installation may vary depending on your system. On Linux you can use your system package manager. On Mac brew install ffmpeg should work.

Usage

Command-Line Interface (CLI)

The CLI expects to find an OpenAI API Key in a OPENAI_API_KEY environment variable, or in a .env file.

Syntax

ttsjoin [OPTIONS] [COMMAND]

Options

Options:
--input-file FILENAME   Plaintext file to process into speech, otherwise stdin
--output-file FILENAME  MP3 result, otherwise stdout
--model TEXT            Slug of the text-to-speech model to be used (tts-1, tts-1-hd or gpt-4o-mini-tts)
--service TEXT          API service (currently only supports openai)
--voice TEXT            Slug of the voice to be used
--instructions TEXT     Voice instructions (only for gpt-4o-mini-tts model)
--no-cache BOOLEAN      Disable caching
--help                  Show this message and exit.

Commands:
  cache [clear, show]

Examples

1. Using an input file and specifying an output file:

# Basic usage with tts-1 model
ttsjoin --input-file input.txt --output-file output.mp3 --model tts-1 --service openai --voice onyx

# Using the new gpt-4o-mini-tts model with instructions
ttsjoin --input-file input.txt --output-file output.mp3 --model gpt-4o-mini-tts --voice ballad --instructions "Speak in a calm, soothing voice"

2. Using stdin and stdout with default options:

echo "Your text to be processed" | ttsjoin > output.mp3

3. Each chunk of text is cached for performance when running the same text multiple times, this can be disabled:

ttsjoin --input-file input.txt --output-file output.mp3 --no-cache

5. Clear cache directory

ttsjoin cache clear

Python Library

You can also use tts-joinery as part of your Python project:

import nltk

from joinery.op import JoinOp
from joinery.api.openai import OpenAIApi

# Only need to download once, handled for you automatically in the CLI
nltk.download('punkt_tab', quiet=True)

tts = JoinOp(
    text='This is only a test!',
    api=OpenAIApi(
        model='tts-1-hd',  # or 'gpt-4o-mini-tts' for the new model
        voice='onyx',
        api_key=OPENAI_API_KEY,
        instructions='Speak in a calm, soothing voice',  # Optional, only for gpt-4o-mini-tts
    ),
)

tts.process_to_file('output.mp3')

Changelog

v1.0.5 (2025-03-20)

• Added support for OpenAI's gpt-4o-mini-tts model and instructions parameter

v1.0.4 (2024-10-11)

• Fixed issue with nltk dependency #4
• Model, voice, and service CLI params are now case-insensitive

v1.0.3 (2024-10-05)

• Added cache management commands to cli
• Fixed a bug when running
• Added end-to-end tests

v1.0.2 (2024-10-03)

• Fixed crash when running with caching disabled (#3)

Contributing

Contributions welcome, particularly other TTS APIs, check the issues beforehand and feel free to open a PR. Code is formatted with Black.

Test can be run manually. Suite includes end-to-end tests with live API calls, ensure you have an OPENAI_API_KEY set in .env.test, and run pytest. You can install development dependencies with pip install -e .[test]

Contributors

Special thanks to:

• Mayank Vishwakarma (@mayankwebbing)

License

This project is licensed under the MIT License.

Copyright 2024, Adrien Delessert