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This is a clone of one real person's voice. Access is by request. CC-BY-NC-4.0: non-commercial use with attribution only. Do not use it to impersonate Daniel Rosehill or to make audio that could be taken as his own words.

Fritter-TTS v1 (GGUF): experimental, for phones and desktops

Quantized GGUF builds of Fritter-TTS v1, a single-speaker text-to-speech fine-tune of Qwen3-TTS-12Hz-1.7B on one voice: Daniel Rosehill, Irish-accented English, with technical and general vocabulary (AI model names, Linux commands, acronyms, version numbers). For qwentts.cpp, a C++/GGML port of Qwen3-TTS that runs on CPU (including Android) and on GPUs through Vulkan.

Experimental. These files have not been listened to against the original model. Automatic checks only (below).

Licence and access. CC-BY-NC-4.0: free for non-commercial use with attribution. Access is by request, because this is a clone of a real person's voice. A personal project by Daniel Rosehill; not affiliated with Alibaba Cloud or NVIDIA.

Files

A voice needs two files: the talker (text to speech codes) and the codec (codes to audio). Use a matching pair.

Quant	Talker	Codec	Peak RAM while speaking	For
Q8_0	`qwen-talker-1.7b-customvoice-Q8_0.gguf` (2.04 GB)	`qwen-tokenizer-12hz-Q8_0.gguf` (291 MB)	~5.8 GB	Desktops; phones with 12 GB+
Q4_K_M	`qwen-talker-1.7b-customvoice-Q4_K_M.gguf` (1.18 GB)	`qwen-tokenizer-12hz-Q4_K_M.gguf` (255 MB)	~4.1 GB	Phones

Checksums are in SHA256SUMS. The voice is the built-in speaker daniel (speaker id 3000); no reference clip is needed. RAM figures are from the same-architecture build of another fine-tune on the same route.

Use

git clone --recursive https://github.com/ServeurpersoCom/qwentts.cpp && cd qwentts.cpp
./buildcpu.sh            # needs OpenBLAS; ./buildvulkan.sh for a GPU; ./buildtermux.sh on Android
echo "Pull the latest image, then restart the container with Docker Compose." | \
  ./build/qwen-tts --model qwen-talker-1.7b-customvoice-Q4_K_M.gguf \
                   --codec qwen-tokenizer-12hz-Q4_K_M.gguf \
                   --speaker daniel --lang English -o out.wav

Output is 24 kHz mono.

How they were made

From Fritter-ASR/Fritter-TTS at d2a95836 (v1), with qwentts.cpp at 5916bf7 (2026-10-16): its convert.py (no changes; it reads the fine-tune's speaker table and tts_model_type) to F32 GGUF, then its quantize tool. The F32 files are not published.

Checks (2026-11-09, automatic only)

The converted talker carries speaker daniel (id 3000) and model_type custom_voice. Not checked: that it sounds like the original by ear, speaker similarity by embedding, or speed.

Base model and licence notices

This model is a build of Fritter-ASR/Fritter-TTS, a fine-tune of Qwen/Qwen3-TTS-12Hz-1.7B-Base, Copyright 2026 Alibaba Cloud, licensed under Apache-2.0 (text in LICENSE-Qwen-Apache-2.0). It was modified by fine-tuning and converted to GGUF for this build.

The CC-BY-NC-4.0 licence above covers the fine-tune and this build; the base model's licence keeps applying to the base model, and nothing here restricts what that licence allows for it.

Not affiliated with or endorsed by Alibaba Cloud.