AI Audio2026
Real‑time full‑duplex speech‑to‑speech system that controls conversational role via text prompts and voice timbre via audio-conditioned embeddings. Built on Moshi; optimized for low-latency, persona-consistent spoken interactions.
AI Audio2026
Generates low-latency, streaming text-to-speech entirely on CPUs (no GPU or cloud API required), using an ~100M-parameter model with voice cloning and multilingual support. Optimized for low resource use (2 CPU cores, ~200ms to first audio chunk) — suited for local, privacy-sensitive, or embedded TTS.
AI Deploy2026
Orchestrates low-latency, multi-stage pipelines for omni and multimodal models by running each stage with its own scheduler and using zero-copy shared memory for tensor transfer. Emphasizes per-stage bottleneck tuning and OpenAI-compatible streaming endpoints, suitable for TTS and multimodal serving.
AI Audio2026
Generates controllable multilingual speech from text with nine predefined timbres and custom-voice control; supports voice design, quick voice cloning and low-latency streaming (first audio packet after a single character), suitable for real-time TTS and voice-design workflows.
AI Audio2026
Local-first voice cloning studio that runs on your machine to clone voices, generate speech in 23 languages, apply audio effects, and compose multi-voice projects. Includes five switchable TTS engines, a REST API, and native GPU/MLX support for privacy-sensitive offline workflows.
AI Audio2026
Provides a Spotify-like local UI for running ACE-Step 1.5 to generate full songs (including vocals), batch variations, and manage a local music library, with reference-audio styling and built-in editing/stem tools for users running the model locally.
AI Audio2026
Generates high‑fidelity, expressive speech and environmental sounds from text. The MOSS‑TTS Family provides specialized models for long‑form TTS, multi‑speaker dialogue, voice design and realtime streaming, plus torch‑free inference paths (llama.cpp / ONNX) and Hugging Face releases.
AI Model2026
Converts text to natural-sounding speech across 600+ languages in a zero-shot way, with short-reference voice cloning and fine-grained voice-design controls; uses a diffusion language-model-style architecture to balance quality and very low inference latency.
AI Audio2026
Zero-shot text-to-speech across 600+ languages with short-reference voice cloning and attribute-based voice design. Uses a diffusion-style discrete non-autoregressive architecture mapping text to multi-codebook acoustic tokens, supports phoneme/pinyin control and very low RTF.
AI Audio2026
Runs local speech-to-text inference for a wide range of ASR model families using GGUF models on the ggml runtime. Supports Metal, Vulkan, and CUDA GPU backends plus a tinyBLAS-accelerated CPU path, prebuilt GGUFs on Hugging Face, and a quantization tool.
AI Audio2026
Local-first voice workflows for cloning, multi-engine TTS/ASR, video dubbing, dictation, transcription and audiobook production across 646 languages. Desktop app with a local OpenAI-compatible API, engine catalogue (TTS/ASR/LLM), and explicit opt-ins for remote features to keep audio and projects on-device.
AI Audio2026
Desktop app for local voice cloning, real-time dictation, and end-to-end video dubbing using zero-shot TTS across 600+ languages; features multi-engine TTS/ASR, speaker diarization, vocal isolation, batch pipelines, and invisible audio watermarking — all run fully offline.