Top 5 Text-to-Speech Open Source Models

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# Introduction

 
Text-to-speech (TTS) technology has advanced significantly, enabling many creators, including myself, to produce audio for presentations and demos with ease. I often combine visuals with tools like ElevenLabs to create natural-sounding narration that rivals studio-quality recordings. The best part is that open-source models are quickly reaching parity with proprietary offerings, providing high-quality realism, emotional depth, sound effects, and even the capability to generate long-form, multi-speaker audio similar to podcasts.

In this article, we will compare the leading open-source TTS models currently available, discussing their technical specifications, speed, language support, and specific strengths.

# 1. VibeVoice

 
VibeVoice is an advanced text-to-speech (TTS) model designed to generate expressive, long-form, multi-speaker conversational audio, such as podcasts, directly from text. It addresses long-standing challenges in TTS, including scalability, speaker consistency, and natural turn-taking. This is achieved by combining a large language model (LLM) with ultra-efficient continuous speech tokenizers that operate at just 7.5 Hz.

The model uses two paired tokenizers, one for acoustic processing and another for semantic processing, which help maintain audio fidelity while allowing for efficient handling of very long sequences. 

A next-token diffusion approach enables the LLM (Qwen2.5 in this release) to guide the flow and context of the dialogue, while a lightweight diffusion head produces high-quality acoustic details. The system is capable of synthesizing up to approximately 90 minutes of speech with as many as four distinct speakers, surpassing the usual limitations of 1 to 2 speakers found in previous models.

# 2. Orpheus

 
Orpheus TTS is a cutting-edge, Llama-based speech LLM designed for high-quality and empathetic text-to-speech applications. It is fine-tuned to deliver human-like speech with exceptional clarity and expressiveness, making it suitable for real-time streaming use cases.

In practice, Orpheus targets low-latency, interactive applications that benefit from streaming TTS while maintaining expressivity and naturalness in its delivery. It is open-sourced on GitHub for researchers and developers, with usage instructions and examples available. Additionally, it can be accessed through multiple hosted demos and APIs (such as DeepInfra, Replicate, and fal.ai) as well as on Hugging Face for quick experimentation.

# 3. Kokoro

 
Kokoro is an open-weight, 82 million-parameter text-to-speech (TTS) model that delivers quality comparable to much larger systems while remaining significantly faster and more cost-efficient. Its Apache-licensed weights allow for flexible deployment, making it suitable for both commercial and hobbyist projects.

For developers, Kokoro provides a straightforward Python API (KPipeline) for quick inference and 24 kHz audio generation. Additionally, there is an official JavaScript (npm) package available for streaming scenarios in both browser and Node.js environments, along with curated samples and voices to evaluate quality and timbre variety. If you prefer hosted inference, Kokoro is accessible through providers like DeepInfra and Replicate, which offer simple HTTP APIs for easy integration into production systems.

# 4. OpenAudio

 
The OpenAudio S1 is a leading multilingual Text-to-Speech (TTS) model, trained on over 2 million hours of audio. It is designed to produce highly expressive and lifelike speech in a wide range of languages. 

OpenAudio S1 allows for fine-grained control over speech delivery, incorporating a variety of emotional tones and special markers (such as angry/excited, whispering/shouting, and laughing/sobbing). This enables an actor-like performance with nuanced expressiveness.

# 5. XTTS-v2

 
XTTS-v2 is a versatile and production-ready voice generation model that enables zero-shot voice cloning using a reference clip of approximately six seconds. This innovative approach eliminates the need for extensive training data. The model supports cross-language voice cloning and multilingual speech generation, allowing users to preserve a speaker’s timbre while generating speech in different languages. 

XTTS-v2 is part of the same core model family that powers Coqui Studio and the Coqui API. It builds on the Tortoise model with specific enhancements that make multilingual and cross-language cloning straightforward.

# Wrapping Up

 
Choosing the right text-to-speech (TTS) solution depends on your specific priorities. Here is a breakdown of some options:

1. VibeVoice is ideal for long-form, multi-speaker conversations, utilizing LLM-guided dialogue turns
2. Orpheus TTS emphasizes empathetic delivery and supports real-time streaming
3. Kokoro offers an Apache-licensed, cost-effective solution that enables fast deployment, delivering strong quality for its size
4. OpenAudio S1 provides extensive multilingual support along with rich controls for emotion and tone
5. XTTS-v2 allows for quick, zero-shot cross-language voice cloning from just a 6-second sample

Each of these solutions can be optimized based on factors such as runtime, licensing, latency, language coverage, or expressiveness.
 
 

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in technology management and a bachelor’s degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.