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Provides an AI-driven English learning app suite (Enjoy) that focuses on speaking practice and pronunciation evaluation. Open-source repo backing a web app, browser extensions for YouTube/Netflix, and a local-first desktop/web client design; some scoring features require the project's paid Enjoy AI service.
Web UI to train and run retrieval-based voice conversion models from small datasets (≈10 minutes), featuring top-1 feature retrieval to avoid timbre leakage, model fusion, real-time conversion, vocal separation, and multi-hardware support.
Local WebUI for video and audio dubbing: download YouTube, isolate vocals, transcribe with Whisper, translate into 100+ languages, and generate multilingual TTS or zero-shot voice clones. Uses Gradio, yt-dlp, Demucs, Whisper/Faster-Whisper, F5/E2/CosyVoice and Edge-TTS; Windows-focused with optional Azure integration.
Generates Netflix-quality single-line subtitles and optional dubbing for videos by automating download, ASR, word-level alignment, translation, terminology management and TTS integration. Emphasizes word-level alignment with WhisperX and cinematic translation/adaptation for cleaner, single-line subtitles and smoother dubbing.
Provides low‑latency on‑device speech-to-text, intent recognition, and text-to-speech for building real‑time voice agents and interfaces. Streaming-optimized models, incremental caching, multilingual TTS/ASR and cross-platform bindings (Python, iOS, Android, Linux, Raspberry Pi) target live voice use cases where sub-200ms responsiveness matters.
Unifies visual creator tools, reusable Skills, and a Codex-powered Agent to handle video translation, image/video generation, voiceovers, and editing in one local multimodal workspace. Desktop and web clients share a synchronized state machine and keep data local by default.
Zero-shot, single‑reference voice cloning TTS with multilingual support (ZH/EN/JA/ES/AR), fine-grained emotion and duration control, and pronunciation hooks (Pinyin/CMU/Kana); ships model weights, Web UI and production deployment recipes for local or server use.
Provides real-time, local audio recording and transcription on macOS using Whisper and Parakeet engines, with global hotkeys and hold-to-record behavior. Includes model download, microphone selection, drag-and-drop file transcription, multilingual auto-detection and Asian-language autocorrect; Apple Silicon only.
Provides text-to-speech synthesis and one-shot voice cloning via compact ONNX models and a larger KittenTTS 2 speech model. Offers CPU-first inference (25–506 MB models), 47 built-in voices, multilingual output, expression tags, streaming, and a Python SDK.
Private, local-first desktop assistant for voice and text conversations that runs models on your hardware. Uses local model servers (Ollama or OpenAI-compatible endpoints), offers personal memory, dictation, TTS/STT, MCP integrations and automatic redaction; free for personal use.
Converts your goals and context into verifiable agent workflows that hill-climb your Current State → Ideal State across life and work. Bundles an ISA-based criteria system, persistent memory and a Pulse dashboard into a single AI-native skill designed to run inside an AI coding harness.
On-device macOS dictation that transcribes speech locally and offers an optional local AI enhancement (Fluid Intelligence) for smart formatting and post-processing. Key features: low-latency model choices, live transcription overlay, per-app prompts and privacy-by-default; best on Apple Silicon.