Projects sharing features with Expo Speech Recognition

PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams into written text without requiring a network connection. It functions as a speech-to-text library, a real-time transcription engine, and a voice command processor, capable of detecting and transcribing spoken commands from continuous audio streams with configurable acoustic and language models. The engine uses weighted finite-state transducers to represent acoustic, phonetic, and language models as a single search graph for efficient decoding. It employs fixed-point acoustic mod

Whishper is a graphical user interface for transcribing audio and video files into text using the Whisper model. It serves as a speech-to-text tool and subtitle file generator that converts spoken content into editable text and timed subtitle formats. The project features an integrated transcription and translation interface, allowing users to refine automated results and convert transcribed text into different languages. It includes a visual editor for correcting speech recognition errors, adjusting segment timecodes, and performing bilingual translation reviews. The system handles the full

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

Auto-subs is an AI transcription and automatic captioning tool that converts spoken audio from video files into synchronized subtitles. It functions as a subtitle generator and a transcription bridge, enabling the conversion of speech to text with automatic speaker identification and multi-language translation support. The software prioritizes data privacy by utilizing on-device AI inference to process audio and video files locally on the user's hardware. It distinguishes itself by offering deep integration with professional video editing workflows, allowing users to export timing and transcr

Foundry-Local is a machine learning development tool designed to facilitate private, on-device inference and model management. It provides a local server environment that hosts machine learning models directly on the user's hardware, ensuring that all data processing, including prompt handling and audio transcription, remains within the local environment without requiring external cloud connectivity. The project distinguishes itself by automating the entire model lifecycle, including the discovery, downloading, and versioning of assets to maintain compatibility with host hardware. It features

Annyang is a speech recognition library and web speech API wrapper that enables the integration of voice command interfaces into websites. It functions as a browser-based voice controller, mapping spoken phrases and regular expressions to specific JavaScript functions to trigger application actions. The library provides mechanisms for voice command mapping and simulation, allowing developers to associate spoken text with executable callbacks. It includes tools for command variable extraction using regular expression capture groups, which allows specific words from a spoken phrase to be passed

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

SmartSub is a cross-platform desktop application for AI-driven video transcription and subtitle generation. It converts audio and video files into text subtitles using local AI models and incorporates hardware acceleration to increase processing speed. The tool features a subtitle translator that leverages large language models, such as OpenAI and DeepSeek, to convert subtitles between different languages. It includes a visual editor for proofreading and polishing transcribed text, paired with a video preview for frame-accurate synchronization. The software supports batch processing of multi

This library is a browser-based utility for real-time voice activity detection. It monitors live microphone input to distinguish between background noise and human vocalizations, enabling applications to identify when a person begins or stops speaking. The project utilizes WebAssembly to execute signal processing logic within the browser sandbox, ensuring high-performance analysis of audio buffers. It integrates directly with the native audio graph to capture raw pulse-code modulation data, employing an energy-threshold approach to identify speech boundaries. The library provides an event-dr

Sherpa-ONNX is an ONNX-based speech processing toolkit that provides a local speech recognition engine, an on-device voice synthesis tool, and a speaker identification framework. It is designed as a cross-platform speech API that enables speech-to-text, text-to-speech, and speaker verification tasks to be executed locally on a device without requiring network access. The project is distinguished by its ability to perform zero-shot voice cloning and speaker diarization on-device. It supports a wide range of hardware accelerations, including GPU and various NPU architectures, and provides a Web

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

This project is a speech recognition and translation engine that utilizes a sequence-to-sequence transformer architecture to convert audio into text. It is built upon a weakly supervised learning framework, which leverages large-scale, unlabelled audio-transcript data to create generalized speech representations capable of performing simultaneous transcription, language identification, and translation. The system distinguishes itself through a unified multi-task modeling approach that shares token sequences across different objectives, allowing it to handle diverse languages and vocabularies

This library provides a deep learning framework for training neural networks to perform speech recognition and audio classification. It utilizes sequence-to-sequence architectures to map variable-length audio inputs into text or numerical outputs, enabling the development of custom speech-to-text transcription models. The project distinguishes itself through integrated audio processing capabilities that transform raw waveforms into spectrograms and high-dimensional numerical vectors. These tools allow for the extraction of unique vocal characteristics to identify speakers, as well as the clas

Whisper Real-Time is a speech-to-text engine designed to convert continuous microphone input into written transcripts. It functions as a real-time audio processor that leverages the OpenAI Whisper model to generate immediate textual output from live spoken language. The system utilizes a transformer-based architecture to map audio sequences to text tokens. It manages incoming data through a sliding-window buffering mechanism and a circular buffer, which ensures a steady stream of audio for the inference engine. To maintain accuracy during continuous processing, the software employs a stateful

CTranslate2 is a C++ inference engine and runtime for Transformer models, designed to execute models on both CPU and GPU with optimizations for speed and memory efficiency. It functions as a model format converter, quantization tool, and REST API server, enabling deployment of neural machine translation, automatic speech recognition, and text generation models. The engine distinguishes itself through a suite of runtime optimizations including layer fusion, weight-matrix quantization, batch-by-length grouping, and a caching allocator that reuses GPU memory. It supports tensor-parallel model di

This project is a hardware-accelerated transcription server and offline subtitle generator. It functions as a speech-to-text tool that converts audio and video files into plain text, JSON, and SRT subtitle formats using the Whisper model. The system operates as an OpenAI Audio API emulator, providing a local server that mimics a specific audio interface. This allows it to serve transcriptions to existing client configurations without requiring changes to the client software. The service utilizes GPU acceleration to increase voice recognition speed and includes utilities for hardware detectio

This project is a deep learning framework designed for end-to-end speech-to-text transcription. It utilizes the WaveNet neural network architecture to process spoken audio input and generate written text transcripts, leveraging connectionist temporal classification to map variable-length audio sequences to character-level outputs. The system distinguishes itself through a comprehensive training pipeline that supports distributed execution across multiple graphics processing units. It includes specialized utilities for audio data augmentation and the transformation of raw audio files into opti

Ecoute is a live transcription tool that provides real-time transcripts for both the user's microphone input (You) and the user's speakers output (Speaker) in a textbox.

Whisper streaming is an automated speech recognition engine designed to convert live audio into text. It functions as a network-based transcription server that accepts raw audio data from remote clients and returns incremental text results in real-time. The system distinguishes itself through its ability to process audio streams incrementally, allowing for immediate transcription and translation as speech is captured. It incorporates voice activity detection to isolate human speech from background noise and utilizes sliding-window buffering to manage incoming audio segments, ensuring that pro

SenseVoice is a multilingual speech large language model designed for audio transcription, speaker diarization, and emotion recognition. It functions as an automatic speech recognition system that converts spoken audio into text across multiple languages. The system distinguishes itself by integrating acoustic event detection and speech emotion recognition, allowing it to identify non-speech sounds, such as laughter or applause, and discrete emotional states. It also includes a framework for speaker diarization to track and label different speakers within a single recording. The project's ca

Buster is a browser extension that solves reCAPTCHA audio challenges by transcribing them into text through speech recognition, and it simulates human-like mouse interactions to bypass visual verification prompts. The extension coordinates with a companion desktop application via local inter-process communication, where the desktop app handles the simulation of natural mouse movements and clicks to improve automated solving success rates. The project distinguishes itself by combining audio transcription with human behavior simulation, using randomized mouse trajectories and timing to mimic hu

Textract is a multi-format text extraction tool and parser. It provides a unified interface to extract plain text from a variety of sources, including documents, images, and audio files. The system functions as a document content parser for PDFs and spreadsheets, an image text extractor using optical character recognition, and a speech-to-text transcriber for audio recordings.

BigBlueButton is an open-source virtual classroom software and meeting server designed for hosting real-time online teaching sessions. It functions as a WebRTC video conferencing platform and collaboration suite, providing a self-hosted environment for virtual classroom management and online course administration. The system distinguishes itself through specialized educational tools, including an interactive quiz engine, breakout room coordination, and live polling. It provides a comprehensive suite of collaborative assets such as a shared infinite whiteboard, real-time co-authored notes, and

Linly-Dubbing is an automated video dubbing pipeline designed for multilingual video localization. It converts spoken content in videos into another language by coordinating speech-to-text transcription, text translation, and text-to-speech synthesis. The system distinguishes itself through AI-driven lip synchronization and animation, which aligns facial expressions and mouth movements to the synthesized voiceover. It also utilizes audio source separation to isolate vocals from background music and noise, allowing for clean voice replacement while preserving original background audio. The br

SmarterStreaming is a cross-platform SDK for hardware-accelerated audio and video capture, encoding, and streaming. It provides a complete media pipeline for low-latency RTMP and RTSP streaming, and includes an embedded lightweight RTSP server that can serve live feeds directly from the source device to local network clients without requiring a separate server. The SDK also integrates with GB28181 surveillance platforms, enabling compliant device registration and streaming for standardized video monitoring systems. The project distinguishes itself through a set of integrated capabilities for