Developer shows how to run Qwen3 TTS locally in real-time with streaming, quantization, word-level alignment, and custom voice fine-tuning for an expressive open-source TTS pipeline.
Heya guys and gals, Around a year ago I released and posted about Persona Engine as a fun side project, trying to get the whole ASR -> LLM -> TTS pipeline going fully locally while having a realtime avatar that is lip-synced (think VTuber). I was able to achieve this and was super happy with the result, but the TTS for me was definitely lacking, since I was using Sesame at the time as reference. After that I took a long break. A week or two ago, I thought to give the project a refresh, and also wanted to see how far we have come with local models, and boy was I pleasantly surprised with Qwen3 TTS. During my initial tests it was lacking, especially the version published by the Qwen team themselves, but after digging around and experimenting a lot I was able to: 1. Make streaming with the model work reliably. The architecture of the model is perfect for this, since the decoder uses a sliding window, which means if you stream the LLM response, that's completely fine and the TTS will keep coherent prosody, pitch, and intonation. 2. Get the model working with llama.cpp, because I am using C# and speed is important, so also quantized it. 3. The model was lacking word-level timings and phonemes which Kokoro (the previous, more robotic sounding TTS) had. So I had to implement CTC word-level alignment to be able to know when certain words are spoken (important for subtitles + getting phonemes to have the lips move correctly). Once this was all done, I also decided to finetune my own Qwen3-TTS voice. The cloning capabilities are really cool, but very lacking in contextual understanding and struggles with pronouncing. Additionally, the custom trained voices provided by the Qwen team didn't have any female native speakers, and I didn't want to create a new Live2D model. In the end, the finetune blew me away and will probably continue improving it. GitHub is here: [https://github.com/fagenorn/handcrafted-persona-engine](https://github.com/fagenorn/handcrafted-persona-engine) Check it out, have fun, and let me know whatever crazy stuff you decide to do with it.
The Qwen3-TTS technical report introduces a series of advanced multilingual text-to-speech models with voice cloning and controllable generation, featuring a dual-track LM architecture and specialized tokenizers for low-latency streaming.
Alibaba's Qwen team releases Qwen3-TTS-12Hz-1.7B-CustomVoice, a powerful text-to-speech model supporting 10 languages with low-latency streaming, instruction-based voice control, and robust contextual understanding.
The developer improved qwen3-tts.cpp to run 5x realtime on RTX 5080 and created a cross-platform desktop GUI with Kotlin Compose Multiplatform, featuring voice cloning, streaming, and speaker embedding management.
Nari Labs introduces Qwen3-TTS and Qwen3-ASR models, providing high accuracy, low latency, and cost-effectiveness in a free public beta, alongside optimized APIs and services for production deployment.
Alibaba's Tongyi Lab released Qwen-Audio-3.0-TTS, a new text-to-speech model with Flash (real-time) and Plus (high-quality) versions, supporting 16 languages, natural language style control, and robust voice cloning.