Moonshine Voice

Voicebox is a local-first, open-source AI voice studio developed in the jamiepine/voicebox repository. It combines voice cloning, text-to-speech, speech-to-text dictation, voice profiles, audio effects, and agent voice output in a desktop application. It generates speech through seven switchable TTS engines, including Qwen3-TTS, Qwen CustomVoice, LuxTTS, Chatterbox, HumeAI TADA, and Kokoro, and supports voice cloning from reference audio, preset voices, multilingual generation, automatic text chunking, crossfading, and multi-track story editing. Whisper-based transcription powers global dictation, in-app recording, and the transcription API; an optional local Qwen3 LLM can refine dictation or rewrite text according to a voice profile's persona. The application exposes REST endpoints for speech generation, agent speech, transcription, and profile management, plus a built-in MCP server with tools for speaking, transcribing, and browsing captures and profiles. It runs models and stores voice data locally, using Tauri with a React/TypeScript frontend and FastAPI backend; platform backends include MLX on Apple Silicon and PyTorch on CUDA, ROCm, XPU, DirectML, or CPU. The repository is licensed under the MIT License and provides macOS, Windows, and Docker distribution, with Linux build-from-source instructions.

Gemma Translator is an open-source, on-device voice-translation application designed to run on a Raspberry Pi 5 with 8GB RAM. It runs the Gemma 4 e2b model locally through LiteRT-LM and uses Moonshine for speech recognition and text-to-speech, providing a two-lane interface for conversations between two people. Each lane records speech, transcribes it, translates it with Gemma, and speaks the result in the other lane’s selected language. The React/Vite frontend communicates with a Python API server and is styled for small displays such as 480×320 kiosk screens. The repository includes model-download, startup, and deployment scripts, production Raspberry Pi OS systemd kiosk service registration, Chromium autostart, and support for development or production modes and landscape active-person or vertical two-operator keyboard layouts. After setup and model download, inference runs without an internet connection.

VoiceStudio is an open-source, fully local desktop application for voice cloning and design, text-to-speech, transcription, dictation, video dubbing, and long-form audio production. It runs on macOS Apple Silicon, Windows, Linux, or Docker and keeps voices, projects, settings, and generated files on the machine by default. The application combines a Tauri desktop shell, a React and Vite interface, and a local FastAPI backend with registries for multiple TTS and ASR engines. Its workflows can transcribe and translate video, preserve speaker assignments, synthesize replacement speech, render audiobook chapters, separate vocals, diarize speakers, process batch jobs, and route work to CPU, CUDA, Apple Silicon MPS/MLX, ROCm, or optional remote workers. It also exposes local REST, SSE, WebSocket, OpenAI-compatible audio, and MCP interfaces, including speech synthesis and transcription endpoints. VoiceStudio is licensed under AGPL-3.0; downloaded models and tokenizers retain their own licenses. The local workflow requires no account, API key, subscription, or usage meter, although remote workers, configured external ASR endpoints, analytics, and other network-backed functions are opt-in. The repository describes the software as an active beta and distributes packaged desktop releases as well as source code.

hayamimi is a local, real-time multilingual speech-to-text tool that produces live subtitles, a browser dashboard, speaker labels, and optional translation without a GPU or cloud API. It detects the language of each utterance and routes it to a dedicated specialist model for Japanese, Chinese, Korean, Cantonese, English, and European languages, with a broad Omnilingual ASR fallback for other languages. The models run as quantized INT8 ONNX models through sherpa-onnx, without PyTorch or CUDA. The pipeline updates partial subtitles while speech is in progress, emits finalized lines shortly after speech stops, and can perform a second batch-decoding pass after silence to produce a refined transcript. Speaker labeling uses CAM++ embeddings and is intended for turn-taking rather than full diarization. The `--serve` option starts a local HTTP server with a live dashboard and an OBS browser-source overlay. Audio can also be supplied over WebSocket, and model eviction keeps resident models below a configurable memory cap, with the default under 2 GB of RAM. The project reports 5.8% character error rate on its Japanese broadcast-audio scorecard and 10–50× real-time processing on a six-core desktop CPU.