simple-tts/README.md

Simple TTS

A simple machine learning text-to-speech program for your terminal. Hear text read aloud by realistic voices; from a file or your clipboard.

Motivation

Text-to-speech is not always supported in many digital platforms out there. The quality is also not consistent.

Having Simple TTS run on the terminal and locally on my machine provides a cozy and private environment I feel safe to use.

This is especially useful for the days when I don't have the mental energy to go through the many written communication or resources I have to, and a little push is needed.

👂 Listen

Features

1. Terminal-first user experience
2. Fully offline
3. Many realistic voices available
4. Use any length of text
5. Saved raw audio files in sensible chunks
6. Use copied text as input
7. Utilize different GPUs as accelerator — Intel architecture supported!

Requirements

Simple TTS is in early development and not packaged or distributed yet for any particular operating system. Please read on to see the tested environment under which I am developing & using it.

1. Debian or Ubuntu - This is currently only tested working on Debian or Ubuntu-based distros.
2. espeak-ng and vlc - The following are required packages aside from the python dependencies. espeak-ng is used under the hood as a fallback engine for English languages, and libvlc is used as the default audio player for the generated audio.
3. Around 55GB of storage - Because it is not yet packaged or compiled, the python dependencies and huggingface models are downloaded separately during the setup process into your machine.
4. Updated drivers for accelerators - GPU accelerators make the program run faster, but you need to have updated drivers for your device that PyTorch requires. However, it will still run fine on CPUs, just slower (up to 2x longer or more).

Setup

First, install the required packages espeak-ng and vlc.

sudo apt update
sudo apt install vlc espeak-ng

Note

Installing vlc via flatpak or snap will not work, as the code need access to libvlc.

Next, clone repo and go into the directory

git clone https://git.ayo.run/ayo/simple-tts
cd simple-tts

Create new Python virtual environment. Here I use conda, but venv is also good.

conda create -n tts

### (optional) for Intel XPU specific device usage:
conda create -n tts --clone llm-pt26

Note

Optional for using Intel XPUs, you need to set up ipex-llm environment with pytorch 2.6. Also, see Intel XPU environmental variables" section below.

Activate the environment and install the dependencies

conda activate tts
pip install -r requirements.txt

Language-specific setup

For some languages, you might need to install specific python dependencies. For example, before you can use Chinese voices to read Mandarin text you have to install the requirements listed in requirements-zh.txt.

# Before using zf or zm prefixed voices...
pip install -r requirements-zh.txt

## then you can use voices for Chinese texts:
python tts.py -v zf_xiaoni "事实胜于雄辩"

## Before using jf or jm prefixed voices...
pip install -r requirements-jp.txt

## then you can use voices for Japanese texts:
python tts.py -v jf_alpha "言い習わし"

Note

You can read more about using different voices in the Voices section.

Intel XPU environmental variables (Optional)

For XPUs, we need to set some environmental variables. I have added a env.sh script which will activate the conda environment tts and set the environmental variables.

. env.sh

Usage

Go into the directory and activate the environment:

cd simple-tts
conda activate tts

If using Intel XPUs, set the env variables

. env.sh

Running the program without arguments will use the demo text tongue-twister.txt with the default voice.

python tts.py # will use default arguments

Providing text inputs

You can pass a string as first argument:

python tts.py "Hello world!" # will be read by the default voice

To run the program with an input file, use flag --input_file.

python tts.py --input_file demo/tongue-twister.txt

# or shorter...
python tts.py -i demo/tongue-twister.txt

You can also use the text stored in your clipboard (i.e., copied text). Select a text from anywhere (e.g., your web browser), copy it with <ctrl>+C or the context menu, then use the flag --clipboard:

python tts.py --clipboard

# or shorter...
python tts.py -c

Labeling your outputs

You can indicate a title to be used as label (i.e., file name prefix and directory name) to the generated outputs using --title. This is useful for organizing your output files and avoid the default temporary named files from being overridden.

# This will put the generated files in ./outputs/simple-greeting/
python tts.py "Hello there!" --title "simple-greeting"
ls ./outputs/simple-greeting

# or shorter
python tts.py "Hello there! and Hi!" -t "simple-greetings"
ls ./outputs/simple-greetings

Voices

You can choose a voice to use with the --voice flag. For this, we use kokoro, which is an Apache-licensed model. See all available voices.

python tts.py --voice am_michael

# or shorter...
python tts.py -v am_michael

There are four shortcuts available to the best voices: pro, hot, asmr, brit (i.e., best trained voices), and pro is the default if no value is given

python tts.py "Hello there!" --voice pro # af_heart

python tts.py "Hello there!" --voice hot # af_bella

python tts.py "Hello there!" --voice asmr # af_nicole

python tts.py "Hello there!" --voice brit # bf_emma

It is possible that the there are additional setup for a specific voice language. If you encounter a problem, please refer to the language-specific setup section ane read the requirements text file for the language you want to use for possible additional steps. For example, using Japanese requires you to choose a dictionary and initialize a configuration file.

Language	lang_code	requirements file
American English	'a'	non additional requirements
British English	'b'	no additional requirements
Mandarin Chinese	'z'	requirements-zh.txt
Japanese	'j'	requirements-jp.txt
Spanish	'e'	no additional requirements
French	'f'	no additional requirements
Hindi	'h'	no additional requirements
Italian	'i'	no additional requirements
Brazilian Portuguese	'p'	no additional requirements

Note

Voices are prefixed with the language code and their gender. For example, 'af' means it is American English and Female. 'zm' means it is Chinese and Male.

Disable audio player

You can disable the built-in audio player with --skip_play if you choose to play the audio files generated with your preferred player.

This is useful for when you just want to generate the audio files, leave your computer running, and come back to it after a while. Don't forget to label your outputs to prevent default named files from being overridden.

python tts.py "Hello there!" --voice asmr --skip_play

# or shorter...
python tts.py "Hello there!" --voice asmr -s

Advanced usages

The --verbose flag can be used to show more informative messages.

python tts.py --verbose

The --device or -d flag can be used to set the desired device (i.e., processor) to use:

python tts.py --device cpu # will use the cpu
python tts.py --device cuda # will use the NVIDIA GPU
python tts.py --device xpu # will use the Intel GPU

If you want to use a voice for a different language text (e.g., Japanese voice for English text) you can use --force_lang

python tts.py -v jf_alpha "Hello there!" --force_lang a

Get help

You can see all available options by running the following:

python tts.py --help

Demo Outputs

Voice: pro (ah_heart)

https://git.ayo.run/ayo/simple-tts/src/branch/main/demo/tongue-twister-af_heart-0.wav

https://git.ayo.run/ayo/simple-tts/src/branch/main/demo/tongue-twister-af_heart-1.wav

https://git.ayo.run/ayo/simple-tts/src/branch/main/demo/tongue-twister-af_heart-2.wav

Voice: asmr (ah_nicole)

https://git.ayo.run/ayo/simple-tts/src/branch/main/demo/tongue-twister-af_nicole-0.wav

https://git.ayo.run/ayo/simple-tts/src/branch/main/demo/tongue-twister-af_nicole-1.wav

https://git.ayo.run/ayo/simple-tts/src/branch/main/demo/tongue-twister-af_nicole-2.wav

Screenshot

Licenses

Simple TTS is BSD 2-Clause licensed.

It uses kokoro, which is an Apache-licensed model.

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Just keep building.
A project by Ayo