Find the Best AI Text-to-Speech Model: F5-TTS, Kokoro, SparkTTS, and Sesame CSM Compared

Want to transform written text into realistic-sounding speech? Large language models have revolutionized AI, and text-to-speech (TTS) technology is rapidly advancing. This article explores four leading open-source TTS models: F5-TTS, Kokoro, SparkTTS, and Sesame CSM. We'll delve into their strengths, weaknesses, and ease of use to help you determine the best option for your needs.

Why are Text-to-Speech Models Important?

TTS models offer exciting possibilities across various applications:

• Content creators can automate voiceovers for videos and podcasts.
• Developers can build accessible and interactive user interfaces.
• Researchers can explore new avenues in human-computer interaction.

Quick Look: TTS Models

Model	Key Features	Strengths	Weaknesses
F5-TTS	Flow matching, Diffusion Transformer	High-quality voice cloning, impressive multi-speaker generation, low word error rate.	Relies on initial audio prompt.
Kokoro	Lightweight, StyleTTS2-based	Extremely fast, efficient, multilingual, excellent handling of punctuation and pauses, sounds human-like.	Lacks native voice cloning capabilities.
SparkTTS	BiCodec, Qwen2.5 LLM	Innovative binary encoding, potential for fine-grained adjustments (pitch, speaking rate).	Voice cloning ineffective, poor handling of punctuation, slower generation in some tests.
Sesame CSM	Multimodal, Residual Vector Quantization	Impressive demonstration of human-like speech, acoustic tokenization of non-verbal vocal cues and tones.	Voice cloning and audio quality of open-source model doesn't quite meet the standard set by F5, complex setup.

Kokoro: The Lightweight Multilingual TTS Champion

Kokoro stands out as a highly efficient TTS model, boasting a mere 82 million parameters. This compact size allows for seamless deployment across diverse environments.

• Multilingual support, including Japanese, Hindi, and Thai.
• Trained on less than 1,000 hours of public domain audio, keeping costs low.
• Generates speech faster than real-time on a DigitalOcean GPU Droplet.

Want to get started? Clone the repository, install the requirements, and launch the web application GUI with these commands:

git clone https://github.com/hexgrad/kokoro
cd kokoro
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
cd demo/
python app.py --share

SparkTTS: An Innovative Approach to Voice Cloning

SparkTTS uses BiCodec, which encodes speech into semantic tokens and speaker attributes to achieve high-quality, zero-shot voice cloning. Use the following code to set up the environment, download all the pretrained model files, and then run the web demo:

git clone https://github.com/SparkAudio/Spark-TTS
cd Spark-TTS/
pip install -r requirements.txt
mkdir pretrained_models
apt-get install git-lfs
cd pretrained_models/
git-lfs clone https://huggingface.co/SparkAudio/Spark-TTS-0.5B
cd ..
python webui.py –device 0

Despite its innovative design, SparkTTS may not be comparable to other SOTA TTS models.

F5-TTS: Top Choice for High-Fidelity Voice Cloning

F5-TTS builds upon its predecessor, E2, using flow matching with a Diffusion Transformer (DiT) for superior results. Its architecture simplifies the process by padding text input to match the length of the input speech. To run F5 TTS, use the following commands:

git clone https://github.com/SWivid/F5-TTS.git
cd F5-TTS
Pip install –upgrade pip
Pip install ffmpeg-python
Apt-get install ffmpeg
pip install -e .
F5-tts_infer-gradio

This will launch the F5 Gradio inference wiki.

Sesame CSM: Bridging the Uncanny Valley

Sesame CSM is a multimodal model that operates on Residual Vector Quantization tokens. The model is remarkably human-like and can speak based on the knowledge of a large language model. To run Sesame CSM, use the following command:

git clone [email protected]:SesameAILabs/csm.git
cd csm
python3.10 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
export NO_TORCH_COMPILE=1

# You will need access to CSM-1B and Llama-3.2-1B
huggingface-cli login

Then, to get access, go to the CSM-1B and Llama-3.2-1B pages. Finally, to execute the script first, run:

python run_csm.py

Which TTS Model is Right for You?

Choosing the ideal text-to-speech model depends on your specific priorities:

• Low Word Error Rate: Consider Kokoro or F5-TTS for accurate and clear speech synthesis.
• Voice Cloning Prowess: F5-TTS excels at replicating voices with impressive fidelity, although Spark is also an option.
• Human-Like Tones: Sesame CSM shines in capturing non-verbal cues, promising remarkably natural-sounding speech.

Final Recommendation

While all four models offer unique strengths, F5-TTS emerges as the overall winner. Its balance of voice cloning, quality, and low error rate make it a top choice for most applications.