Search Results for "define"

...It is built around conversational large language models and Azure based text to speech services, turning them into an interactive environment for speaking practice in multiple languages. Users can define custom AI personas, choose languages, and configure their own OpenAI and Azure keys so they retain control over which backends they use. The app supports speech recognition with quick keyboard shortcuts, allowing learners to hold down a key to speak and release it to submit for recognition and response. It includes translation features, dark mode, playback of the user’s own recorded speech, and word highlighting that tracks the progress of synthesized audio to make following along easier. ...

...It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state of the art architectures such as recurrent neural networks, Transformer models, variational autoencoder hybrids, and multi task systems. Lingvo includes reference models and configurations for domains like machine translation, automatic speech recognition, language modeling, image understanding, and 3D object detection. ...

...It is built as a Gradio Python demo, exposing a web interface where users can talk to an animated avatar that lip-syncs to synthesized speech while responding intelligently. The system is customizable: you can define your own avatar appearance and voice, and it supports voice cloning so you can generate a new voice from a short 3–10 second reference sample. The tech stack integrates FunASR for speech recognition, Qwen for language understanding, multiple TTS engines like GPT-SoVITS, CosyVoice, or edge-tts, and MuseTalk for talking-head generation.

...It lets you hold natural conversations with AI characters that can see, listen, and speak, while expressing emotional states through facial expressions and body language. Users can import VRM character models, adjust their appearance, tune the voice to match the character, and define behavior using different large language models and TTS backends. Under the hood, Amica leverages modern web and desktop technologies: three.js and three-vrm for 3D rendering, Transformers.js for running models in the browser, Whisper and Silero VAD for speech recognition and voice-activity detection, and a variety of LLM backends such as llama.cpp servers, ChatGPT-compatible APIs, Ollama, KoboldCpp, and others. ...