Projects sharing features with RealtimeVoiceChat

Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag

Sherpa-ncnn is an edge-based speech recognition and synthesis engine designed to run neural network models locally on mobile, embedded, and desktop hardware. It provides a cross-platform framework for offline speech-to-text transcription and text-to-speech synthesis, ensuring that all audio processing occurs on-device without requiring an internet connection or external cloud services. The project distinguishes itself through its use of the ncnn inference engine, which is optimized for low-latency execution on resource-constrained devices. It incorporates on-device model quantization to reduc

This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu

LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections. The platform distinguishes itself through it

Ten Framework is a multimodal large language model agent framework designed for building low-latency conversational agents. It integrates voice, text, and visual inputs in real time to facilitate human interaction. The project includes a real-time speech processing pipeline for streaming transcription, voice activity detection, and speaker diarization. It also features an avatar synchronization engine that coordinates character lip animations and visual outputs with synthesized speech. The framework covers edge AI deployment through containerized packaging and direct integration with embedde

Fonoster is a conversational AI framework and multi-tenant communications platform as a service. It serves as a programmable voice gateway and SIP telephony platform, enabling the creation of voice-based assistants and automated communication workflows using large language models. The project distinguishes itself through a vendor-agnostic speech integration engine that abstracts speech-to-text and text-to-speech providers. It features a multi-tenant architecture that isolates telephony resources and user identities into distinct organizational workspaces. The system covers a broad range of t

MoneyPrinterPlus is an automated video production system designed for the mass creation of short-form AI content. It functions as an end-to-end pipeline that uses large language models to generate scripts, synthesize voiceovers, and produce visual assets to assemble complete videos. The project is distinguished by its ability to batch-process high volumes of unique content through automated mixing and randomized asset pairing. It includes a social media auto-publisher that uses browser simulation to automate the upload and distribution of generated videos to platforms such as TikTok and Xiaoh

LiveTalking is an interactive talking head engine and AI avatar management platform designed to synchronize synthetic speech with facial movements. It functions as a real-time orchestrator that connects large language models and text-to-speech services to neural-rendered digital humans. The project distinguishes itself through low-latency streaming capabilities and the ability to handle real-time conversational interruptions. It supports advanced audio-visual customization, including human voice cloning and the ability to drive avatar expressions using real-time webcam data. The platform cov

Vocode-python is an LLM voice AI framework and orchestration library used to build real-time conversational agents. It functions as a speech-to-speech pipeline that integrates large language models with speech-to-text and text-to-speech services to facilitate continuous spoken dialogue. The framework acts as a telephony integration gateway, connecting voice agents to phone lines and video conferencing platforms through automated calling infrastructure. It provides the means to deploy voice channels to external communication platforms and host telephony servers. The library manages the end-to

Kimi-Audio is a large language model audio foundation model designed to understand audio input and generate high-fidelity speech responses in real time. It functions as a unified system encompassing a text-to-speech synthesis engine and a speech-to-text transcription tool. The project enables real-time audio conversations through a multi-modal conversation loop and chunk-wise streaming detokenization to reduce playback latency. It provides controls over speech speed, accent, and emotional tone during conversational audio generation. The system covers audio intelligence capabilities, includin

Streamer-Sales is a digital avatar video generator and large language model sales agent framework. It functions as a multimodal AI pipeline that synthesizes talking-head videos using text-to-speech and face animation to create virtual spokespeople. The system differentiates itself by combining retrieval-augmented generation with agentic web searching to ground product descriptions and sales scripts in factual data and real-time information. It further integrates a multimodal interaction workflow that coordinates automatic speech recognition and text-to-speech for real-time voice conversations

This project is a framework for building local voice assistants and a real-time audio streaming server. It functions as a containerized inference engine and a multilingual speech pipeline that orchestrates speech-to-text, language models, and text-to-speech components to convert spoken input into spoken output. The system is distinguished by its use of WebSocket-based bidirectional streaming for low-latency interactions. It features a voice activity detection system that manages speech boundaries and handles user barge-in interruptions during assistant playback. It also supports custom voice

01 is a voice-to-code agent and language model voice interface framework that enables natural language control of computers and devices. It functions as a real-time audio streaming server and a cross-platform voice client, translating spoken instructions into executable code to automate software, manage files, and browse the web. The system supports both local and cloud-based language models, alongside local or hosted speech-to-text and text-to-speech engines. It is designed for custom hardware integration, providing the means to build embedded AI voice controllers using microcontrollers like

Duix-Mobile is a software development kit for deploying real-time conversational AI characters on mobile devices. It enables the creation of interactive digital humans capable of fluid voice-to-voice interactions, featuring low-latency speech recognition and synchronized lip movements. The project distinguishes itself through the ability to integrate custom external language models and speech providers to define an avatar's intelligence and voice. It supports the generation of real-time multilingual subtitles and provides mechanisms to track the training status of newly created digital charac

Omi is an open-source wearable AI platform that captures audio and screen data to provide real-time conversational assistance and memory. It integrates a wearable hardware development kit with a vector memory database and large language model capabilities to create a persistent digital record of user interactions. The platform is distinguished by its BLE audio streaming pipeline, which transmits raw audio from wearable hardware for real-time transcription and speaker identification. It utilizes a plugin-based agent tool framework that allows AI assistants to autonomously invoke custom functio

The Gemini Cookbook is a comprehensive collection of implementation patterns, code samples, and development guides designed for building applications with Google Gemini models. It serves as a central resource for developers to integrate multimodal generative artificial intelligence into their software, providing the necessary frameworks to manage model interactions, stateful workflows, and structured data extraction. The repository distinguishes itself by offering specialized toolkits for autonomous agent orchestration, enabling the construction of agents that can execute code, browse the web

Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

Personaplex is an LLM speech-to-speech framework and conversational AI persona engine designed for real-time voice interfaces. It provides a system for defining AI identities and vocal characteristics through a combination of text-based role prompts and audio reference files. The project features a real-time AI voice interface that supports full-duplex human-AI dialogue, enabling multiple parties to speak and listen simultaneously via bidirectional audio streaming. It includes a GPU-accelerated audio processor and a speech-to-speech pipeline to facilitate low-latency conversations. The frame

This project is a comprehensive suite for neural speech synthesis, featuring a deep learning text-to-speech engine, a neural speech synthesis trainer, and a voice cloning toolkit. It provides a system for synthesizing human-like speech from text using neural network models and high-fidelity vocoders. The suite includes a speech model conversion utility to transform deep learning models between different formats for deployment across various hardware runtimes. It also provides a self-contained HTTP server to expose pre-trained text-to-speech models as a remote audio API. Capabilities include

This project is a deep learning text-to-speech toolkit used for training and deploying neural speech synthesis models. It provides a comprehensive framework for converting written text into spoken audio, utilizing neural vocoders to transform synthesized spectrograms into high-fidelity audio waveforms. The toolkit includes a voice cloning system that replicates specific human voices by extracting speaker embeddings from short audio samples. It also supports multi-speaker audio synthesis, allowing the generation of speech across different vocal identities using specialized model architectures.

ChatTTS-ui is a web-based interface and API wrapper for the ChatTTS model, designed to convert written text and mixed language input into spoken audio. It functions as an AI speech synthesis dashboard and a programmatic generator for creating naturalistic voice output. The project focuses on custom voice profiling and speech nuance control. It allows for the maintenance of consistent speaker characteristics using seed values and data files, while providing controls for tone, laughter, and pauses through behavioral prompts and sampling parameters. The system includes a client-server architect

Julius is a high-performance, open-source speech recognition engine designed for large vocabulary continuous speech recognition. It functions as a comprehensive framework utilizing Hidden Markov Model-based acoustic modeling and N-gram language models to convert live or recorded audio into text. The engine is built to support real-time streaming and provides a network-accessible service that allows external applications to manage recognition sessions and receive transcription results through programmatic commands. The engine distinguishes itself through its modular architecture and support fo

RealtimeSTT is a local speech-to-text engine and real-time automatic speech recognition server. It utilizes transformer-based recognition and omnilingual pipelines to convert live audio streams into text, providing a WebSocket-based streaming API for raw PCM audio transmission. The project is distinguished by a dual-backend transcription pipeline that uses a lightweight engine for immediate partial suggestions and a heavier model for final high-accuracy results. It includes a wake word detection system to trigger recording and employs a shared-resource inference model to distribute heavy spee