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# Introduction
Text-to-speech (TTS) technology has advanced significantly, enabling many creators, including myself, to produce audio for presentations and create demos with ease. I often combine visuals with tools like Eleven Labs to create a natural-sounding narrative that rivals studio-quality recordings. Best of all, open-source models are quickly catching up with proprietary offerings, providing high-quality realism, emotional depth, sound effects and even the ability to produce long-form, multi-speaker audio like podcasts.
In this article, we will compare the currently available open source TTS models, discussing their technical specifications, speed, language support and specific strengths.
# 1. vibevoice
vibevoice is an advanced text-to-speech (TTS) model designed to produce 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 taking natural turns. This is achieved by combining a large language model (LLM) with ultra-efficient persistent speech tokenizers that operate at only 7.5 Hz.
The model uses two coupled tokenizers, one for acoustic processing and one for semantic processing, which helps maintain audio fidelity while allowing very long sequences to be handled efficiently.
The next token diffusion approach enables LLM (QWEN2.5 in this release) to guide dialogue flow and context, while lightweight diffusion produces high-quality acoustic details. The system is capable of synthesizing up to 90 minutes of speech with up to four separate speakers, surpassing the usual 1 to 2 speaker limitations found in previous models.
# 2. Orpheus
Orpheus TTS is a modern, Llama-based speech LLM designed for high-quality and empathetic text-to-speech applications. Fine to render 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 the expressiveness and naturalness of its delivery. It is open to researchers and developers on GitHub, with usage instructions and examples available. Additionally, it can be accessed from multiple hosts of demos and APIs (such as Dipenfra, Replication, and FAL.AI), as well as face-hugging for quick experiments.
# 3. Kokoro
Kokoro is an open-weighted, 82-million-parameter text-to-speech (TTS) model that provides quality comparable to much larger systems while remaining significantly faster and cost-effective. Its Apache-licensed weights allow for flexible deployment, making it suitable for both commercial and hobby projects.
For developers, Cocoro provides a straightforward Python API (KPipeline) for quick diagnosis and 24 kHz audio generation. Additionally, there is an official JavaScript (npm) package available for scenarios in both the browser and Node.js environments, with samples and sounds designed to evaluate quality and timbre types. If you prefer hosted indicators, Kokoro is accessible through providers such as DeepInfra and Replication, which offer simple HTTP APIs for easy integration into production systems.
# 4. Open Audio
OpenAudio S1 An important multilingual text-to-speech (TTS) model, trained on over 2 million hours of audio. It is designed for highly expressive and life-long speech in a wide range of languages.
OpenAudio S1 allows fine-grained control over speech delivery, including multiple emotional tones and special markers (such as angry/excited, whisper/scream, and laugh/sob). It enables an actor-like performance with expressive expression.
# 5. XTTS-V2
XTTS-V2 A versatile and production-ready voice generation model that enables zero-shot voice cloning using an approximately six-second reference clip. 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 the speaker’s timbre while generating speech in different languages.
XTTS-V2 is part of the same core model family that powers Cookie Studio and the Cookie API. It builds on the Tortoise model with some special enhancements that make multilingual and cross-language cloning straightforward.
# wrap up
Choosing the right text-to-speech (TTS) solution depends on your specific preferences. Here is a breakdown of some options:
- VibeVoice is ideal for long-form, multi-speaker conversations, utilizing the LLM-directed turn
- Orpheus TTS emphasizes empathetic delivery and supports real-time streaming
- Cocoro offers an Apache-licensed, cost-effective solution that enables rapid deployment, delivering robust quality for its size.
- OpenAudio S1 offers extensive multilingual support with rich control of emotion and tone
- The XTTS-V2 allows instant, zero-shot cross-tongue sound 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 Owan For centuries.@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 create an AI product using graph neural networks for students with mental illness.