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Builds realtime voice AI agents that run as server-side participants in WebRTC rooms — mix STT, LLM, and TTS providers or use one realtime model. Adds semantic turn detection, SIP telephony, multi-agent handoffs, and an LLM-judge test harness.
Builds real-time voice and multimodal AI agents as composable streaming pipelines. Vendor-neutral: swap among 20+ STT, 20+ LLM and 30+ TTS providers over WebRTC or WebSockets, and compose multi-agent systems with handoff and parallel workers.
Lets AI agents place and answer business phone calls, holding spoken conversations to collect structured data, answer questions, and escalate to humans. Built on Azure Communication Services and Azure OpenAI, with RAG over your own documents.
Clones a voice from a 5-second sample for zero-shot TTS, or fine-tunes on ~1 minute of audio for few-shot synthesis. Covers Chinese, English, Japanese, Korean, and Cantonese, with a WebUI bundling vocal separation, ASR, and dataset labeling.
BYOK desktop app working as a universal MCP client: run any MCP server against OpenAI, Anthropic, Gemini, Grok, Ollama and 10+ providers. Also offers prompt-anywhere, AI text commands, local-file RAG, media generation and voice input.
Provides leaderboard-ready test splits for the Open ASR Leaderboard: converts unsafe custom loaders to Parquet, sorts samples by audio length, and packages eight ESB test sets (LibriSpeech, Common Voice, GigaSpeech, SPGISpeech, etc.) for reproducible ASR benchmarking.
Chains four swappable open modules — voice activity detection, speech-to-text, an LLM, and text-to-speech — into a local voice agent that needs no proprietary APIs. Runs on CUDA, Apple Silicon, or Docker, with an OpenAI-compatible realtime WebSocket mode.
Runs local LLM, vision-language, ASR, OCR, and image-generation models across NPU, GPU, and CPU from one command. Differs from Ollama and llama.cpp with first-class Qualcomm Hexagon NPU support and day-0 coverage of new models like Qwen3-VL.
VideoCaptioner is an AI-powered video subtitling assistant that combines ASR (local or cloud) with LLM-based subtitle segmentation, correction and translation. It supports offline GPU transcription, concurrent chunk transcription, VAD, speaker-aware processing, batch subtitling and one-click subtitle-to-video synthesis, with both GUI and CLI options.
Press a configurable shortcut, speak, and have your words transcribed and pasted into the active app. Runs Whisper or the CPU-friendly Parakeet V3 fully offline; a Tauri + Rust build with Silero voice-activity detection and optional GPU acceleration.
Turns OpenAI Whisper into a live streaming transcriber: audio flows in over WebSocket and text returns word-by-word instead of after full utterances. Adds SimulStreaming and LocalAgreement decoding, Silero VAD, and speaker diarization, all self-hosted.