Projects sharing features with Voicebox

Vocode-core is a framework for building real-time conversational AI voice agents. It serves as a conversational orchestrator and pipeline that integrates speech-to-text, large language models, and text-to-speech services to enable low-latency voice interactions. The project features a provider-agnostic interface that allows for swappable speech and language model providers, including support for both cloud APIs and local binaries. It distinguishes itself through a specialized telephony integration layer that enables agents to be deployed across phone lines, WebRTC, and virtual meeting platfor

VoxCPM is a multilingual speech synthesis system and text-to-speech inference server. It functions as an AI voice cloning tool and a synthetic voice designer, capable of generating natural speech across global languages and regional dialects using a GPU-accelerated audio generator. The project features a speech model fine-tuning framework that supports both full parameter updates and low-rank adaptation for customizing voice characteristics. It enables high-fidelity voice cloning from reference audio, including cross-lingual voice transfer and acoustic environment mimicry, as well as the crea

Tortoise-tts is a neural text-to-speech engine and voice cloning toolkit designed for high-quality audio generation. It functions as a zero-shot synthesis system, meaning it can generate speech for unseen speakers without requiring additional training or fine-tuning for each new voice. The system specializes in replicating human vocal characteristics using small sets of reference audio clips. It allows for the extraction of voice latents to mimic specific speakers, the generation of random synthetic identities, and the blending of multiple voice profiles to create hybrid vocal identities. Th

EmotiVoice is an emotional text-to-speech engine and bilingual speech synthesizer designed to generate synthetic audio in English and Chinese. It utilizes a deep learning architecture to produce high-fidelity speech with controllable emotional states and timbres. The project includes a voice cloning framework for replicating specific speaker identities by training custom acoustic models on personal audio datasets. It employs a jointly-trained acoustic-vocoder pipeline and style-embedding-based synthesis to manage expression and reduce audio artifacts. The system covers a broad range of speec

This project serves as a curated directory and resource hub for developers working with generative artificial intelligence. It provides a comprehensive index of open-source software solutions, frameworks, and project examples designed to help users discover and implement advanced AI systems. The repository focuses on practical implementations of agentic, multimodal, and retrieval-augmented generation architectures. It highlights tools for building conversational assistants, voice-enabled agents, and automated workflows that leverage large language models. By showcasing diverse technical domai

This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services

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

F5-TTS is a text-to-speech system that utilizes a flow matching engine and diffusion transformers to generate fluent synthetic speech. It functions as a multilingual speech synthesizer and neural training framework, providing tools for voice cloning and high-performance inference serving. The project distinguishes itself through a voice cloning toolkit capable of mimicking specific speaker characteristics and tones from reference audio clips. It supports cross-lingual generation, allowing for the synthesis of audio across various global languages or the mixing of multiple languages within a s

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

Chatterbox is a comprehensive machine learning platform designed for multilingual speech synthesis and real-time audio generation. It functions as an engine that converts text into natural-sounding speech, capable of replicating specific human vocal characteristics and emotional expressions from short audio samples. The platform distinguishes itself through advanced control over the synthesis process, allowing for the manipulation of emotional intensity and the injection of non-verbal vocalizations such as laughter or coughing. It is engineered for low-latency performance, utilizing an optimi

This project is a generative speech synthesis engine that converts text into high-fidelity human speech. It utilizes a two-stage autoregressive transformer architecture that separates semantic token prediction from acoustic detail reconstruction to balance linguistic accuracy with audio quality. The system is designed to support multilingual output and conversational AI development, enabling the generation of context-aware speech that maintains flow across multiple dialogue turns. The platform distinguishes itself through a production-ready inference server that employs continuous batching to

This project is a comprehensive toolkit for on-device speech recognition, synthesis, and audio processing, specifically engineered for Apple Silicon. It provides a framework for building real-time, full-duplex voice agents that operate entirely offline, leveraging native hardware acceleration to maintain performance and privacy. By utilizing optimized machine learning models, the library enables local execution of complex audio tasks without reliance on external cloud services. The library distinguishes itself through its specialized focus on local, high-performance voice interaction. It incl

Pyvideotrans is an automated video localization platform designed to transcribe, translate, and dub media content for international distribution. It functions as an end-to-end workflow that combines speech recognition, text translation, and synthetic voice generation to process video files into localized versions. The system distinguishes itself by offering a choice between local model inference for privacy and integration with third-party cloud services via user-provided credentials. This architecture allows users to maintain control over their billing and data security while utilizing modul

This project is a GPU-accelerated speech engine and AI voice cloning tool. It functions as a text-to-speech synthesizer and voice-to-voice converter that replicates specific human voices to generate synthetic speech. The system creates digital voice profiles by analyzing short audio samples or capturing live microphone input. These profiles enable the transformation of existing audio recordings into a target speaker's voice or the synthesis of new audio from written text. The engine supports subtitle-based speech generation for batch processing and automated dubbing workflows. A web-based au

MockingBird is an AI voice cloning tool and text-to-speech system designed to generate synthetic speech. It functions as a voice synthesis trainer for building custom models from audio datasets, a command-line generator for producing audio files, and a text-to-speech server for remote application integration. The project specializes in real-time voice cloning, which extracts vocal characteristics from short audio samples to mimic a target speaker's unique timbre. It utilizes reference-driven audio synthesis to condition pre-trained models on specific audio samples, allowing for the generation

Handy is a local speech-to-text automation tool designed to convert spoken audio into text and inject it directly into active desktop applications. By running machine learning models entirely on the host hardware, it provides a private, offline-first environment for dictation and command execution. The system functions as a background service that manages microphone input, transcription state, and text output, enabling hands-free typing across various software environments. The project distinguishes itself through a modular pipeline that integrates local language models for post-transcription

all-in-one is a containerized deployment system designed to install and manage a complete suite of productivity and collaboration services. It functions as a cloud suite deployer that orchestrates the installation of a self-hosted content platform, incorporating necessary dependencies via Docker or Kubernetes. The project distinguishes itself by providing a web-based dashboard for orchestrating, updating, and monitoring the lifecycle of service containers. It also serves as a local AI inference server, enabling the execution of generative text models, image diffusion, and speech processing on

This project is a self-hosted meeting transcription and summarization tool that converts audio recordings into text transcripts and structured notes using large language models. It functions as an enterprise meeting documentation manager, allowing for the organization and editing of timestamped records. The system prioritizes data privacy through local-first processing and the ability to deploy on private infrastructure. It supports a provider-agnostic architecture, enabling users to connect to local AI engines, self-hosted servers, or cloud-based API endpoints for both transcription and summ

Buzz is a desktop application that provides a local speech-to-text engine for transcribing and translating audio and video files. By leveraging local machine inference, the software ensures data privacy and offline performance, removing the need for cloud connectivity during media processing. The application distinguishes itself through a modular plugin architecture that allows for the integration of custom functionality, such as content summarization and automated text formatting, without modifying the core codebase. It also features a speaker diarization pipeline that identifies and labels

MiniCPM-V is a multimodal large language model and vision-language system designed for complex visual and linguistic understanding. It functions as an on-device AI model, providing the capacity to process text, images, and video as a compact neural network. The project is specifically developed as an edge AI framework, utilizing quantization and weight sharding to run on memory-constrained mobile chipsets. This allows for the deployment of multimodal intelligence directly on mobile operating systems for local inference. Its capabilities cover multimodal content analysis of high-resolution im

VoiceInk is a system-wide speech-to-text dictation tool that converts spoken audio into text using local or cloud AI models. It functions as a local AI transcription engine and a context-aware voice assistant, allowing users to insert transcribed text directly into any active application on the operating system. The project distinguishes itself through the use of custom vocabulary management, which trains transcription engines to recognize industry-specific technical terms, professional terminology, and personal names. It further enhances output by using large language models to refine raw tr

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

OpenVINO is an AI inference engine and model serving platform designed to execute optimized deep learning models across CPUs, GPUs, and NPUs through a unified API. It includes a model optimization toolkit for converting, quantizing, and compressing models from various frameworks, alongside a specialized generative AI runtime for large language models. The project distinguishes itself through a plugin-based hardware acceleration layer that maps neural network operations to vendor-specific drivers. It features advanced execution mechanisms such as continuous batching, speculative decoding, and

Pocket-tts is a text-to-speech server and neural speech synthesizer that converts written text into audible speech. It includes a CPU-optimized inference engine and a voice cloning tool capable of analyzing audio samples to reproduce specific speaker characteristics. The system differentiates itself through the use of dynamic int8 quantization to reduce memory usage and increase generation speed on processors. It supports real-time speech synthesis by streaming audio chunks incrementally and utilizes voice state caching to store processed embeddings as portable files, bypassing redundant proc

Piper is a local neural text-to-speech engine designed to convert written text into natural human speech entirely on your own hardware. By utilizing a neural synthesis framework, it operates without the need for internet connectivity, ensuring that all audio generation remains private and secure. The system distinguishes itself through a modular architecture that allows for the dynamic loading of speaker embeddings and voice configurations. This enables users to switch between various vocal personas and styles without requiring a full reload of the core synthesis model. By processing input th