Open Source Windows Speech Recognition Software
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Speech Recognition Software for Windows
View 36 business solutionsBrowse free open source Speech Recognition software and projects for Windows below. Use the toggles on the left to filter open source Speech Recognition software by OS, license, language, programming language, and project status.
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples. whisper.cpp supports integer quantization of the Whisper ggml models. Quantized models require less memory and disk space and depending on the hardware can be processed more efficiently. -
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CMU Sphinx
Speech Recognition Toolkit
Thank you for visiting! ----> Maintenance and improvement work has MOVED to https://cmusphinx.github.io/ Please go there for the most recent software and documentation. <---- CMUSphinx is a speaker-independent large vocabulary continuous speech recognizer released under BSD style license. It is also a collection of open source tools and resources that allows researchers and developers to build speech recognition systems. -
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented as a sequence of tokens to be predicted by the decoder, allowing a single model to replace many stages of a traditional speech-processing pipeline. The multitask training format uses a set of special tokens that serve as task specifiers or classification targets. -
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VideoSrt
Windows-GUI
This is an open source Windows-GUI software tool that can recognize video speech and automatically generate subtitle SRT files. VideoSrtIt is written in Golanglanguage and developed based on lxn/walk Windows-GUI toolkit. Open source software tool that can recognize video speech and automatically generate subtitle SRT files. It is suitable for business scenarios that quickly and batch generate Chinese/English subtitles and text files for media (video/audio). Recognize video/audio speech to generate subtitle files (support Chinese-English translation, bilingual subtitles) Extract speech text from video/audio. Batch translation, filter processing/encoding SRT subtitle files. Using the Alibaba Cloud speech recognition interface, the accuracy is high, and the standard Mandarin/English recognition rate is over 95%. Video recognition does not need to upload the original video, which is convenient, fast and time-saving. -
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Buster
Captcha solver extension for humans
Save time by asking Buster to solve captchas for you. Buster is a Firefox extension which helps you to solve difficult captchas by completing reCAPTCHA audio challenges using speech recognition. Challenges are solved by clicking on the extension button at the bottom of the reCAPTCHA widget. It is not guaranteed that challenges are always solved, the limitations of the technology need to be considered. The continued development of Buster is made possible thanks to the support of awesome backers. If you'd like to join them, please consider contributing with Patreon, PayPal or Bitcoin. The success rate of the extension can be improved by simulating user interactions with the help of a client app. Follow the instructions from the extension's options to download and install the client app on Windows, Linux and macOS, or get the app from this repository. -
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OpenVINO
OpenVINO™ Toolkit repository
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi. -
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Google2SRT
Download, save and convert multiple subtitles from YouTube videos
Google2SRT allows you to download, save and convert multiple subtitles and translations from YouTube and Google Video to SubRip (.srt) format, which is recognized by most video players. You can download XML subtitles or simply type video's URL, Google2SRT will do the rest. -
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Speech recognition research toolkit
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This includes the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. That’s why training data is required for many modern machine learning use cases including computer vision, natural language processing and speech recognition. -
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VoiceCommander 2.0 Multilingual Offline
2.0 Offline multilingual voice control for Windows. Fast, private
Release 2,0 : Full project website: https://voicecommander2multilingual.sourceforge.io/ Return any reviews or problem to : ducktheapp@gmail.com VoiceCommander Multilingual Offline is a local voice command system for Windows, focused on speed, privacy, and simplicity. It runs entirely on your PC with no cloud services, no external APIs, and no internet connection. All voice recognition and commands are processed locally, ensuring full control of your data. The software allows you to control your computer using voice commands in multiple languages, including launching applications, managing system functions, and interacting with Windows. Features: - 100% offline (no cloud, no data sharing) - Multilingual voice commands - Control apps, browser, and system - OCR + text-to-speech screen reading - Portable (no installation) - No registry changes NVIDIA GPU recommended (GTX 1060+). CPU mode supported (slower). For any other information please contact : Ducktheapp -
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VoiceCommander Multilingual Offline
Offline multilingual voice control for Windows. Fast, private, local.
Return any reviews or problem to : ducktheapp@gmail.com VoiceCommander Multilingual Offline is a local voice command system for Windows, focused on speed, privacy, and simplicity. It runs entirely on your PC with no cloud services, no external APIs, and no internet connection. All voice recognition and commands are processed locally, ensuring full control of your data. The software allows you to control your computer using voice commands in multiple languages, including launching applications, managing system functions, and interacting with Windows. Features: - 100% offline (no cloud, no data sharing) - Multilingual voice commands - Control apps, browser, and system - OCR + text-to-speech screen reading - Portable (no installation) - No registry changes NVIDIA GPU recommended (GTX 1060+). CPU mode supported (slower). A practical alternative to cloud-based voice assistants. For any other information please contact : ducktheapp@gmail.com The Duck -
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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to experiment with new algorithms, as well as for practitioners who want robust, production-ready ASR pipelines. It includes extensive tools for data preparation, feature extraction, acoustic and language modeling, decoding, and evaluation. With its modular design, Kaldi allows users to adapt the system to a wide range of languages and domains. As one of the most influential projects in speech recognition, it has become a foundation for much of the modern work in ASR. -
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WhisperJAV
A subtitle generator for Japanese Adult Videos.
A subtitle generator for Japanese Adult Videos. Transformer-based ASR architectures like Whisper suffer significant performance degradation when applied to the spontaneous and noisy domain of JAV. This degradation is driven by specific acoustic and temporal characteristics that defy the statistical distributions of standard training data. -
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Scribe
Free, open-source, and offline speech-to-text & voice control app.
> Scribe is a free and open-source desktop assistant that brings powerful speech-to-text and voice control capabilities directly to your PC. It allows you to dictate text into any application, create custom voice commands, launch programs, and automate your workflow with text replacements. > Designed with privacy as a top priority, Scribe works completely offline. Your voice data never leaves your computer. Powered by the Vosk engine, it supports multiple languages and provides high-quality recognition without an internet connection. > Scribe is the perfect tool for anyone looking to boost productivity, improve accessibility, or simply interact with their computer in a new, hands-free way. -
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Comandi Vocali Offline per Windows
Sistema comandi vocali offline per Windows, veloce e privato .Offline
Questa versione è superata. 👉 Nuova versione funzionante: https://voicecommander2multilingual.sourceforge.io/ o scaricala direttamente - direct download : https://sourceforge.net/projects/voicecommander2multilingual/files/VoiceCommander2.zip/download VoiceCommander 2.0 è stabile, migliorato e completamente operativo. Comandi Vocali Offline per Windows è un sistema di controllo vocale che funziona interamente in locale sul tuo PC. Permette di controllare il computer con la voce senza connessione internet, senza cloud e senza inviare dati all’esterno. Il sistema è progettato per garantire massima privacy, velocità e semplicità. Caratteristiche principali: - Funziona completamente offline (nessun server, nessun cloud) - Riconoscimento vocale veloce con modelli locali - Controllo di browser, programmi e sistema - Lettura dello schermo tramite OCR e sintesi vocale - Installazione semplice senza modifiche al registro - Portabile e removibile -
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Lip Reading
Cross Audio-Visual Recognition using 3D Architectures
The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the extracted information from one modality to improve the recognition ability of the other modality by complementing the missing information. The essential problem is to find the correspondence between the audio and visual streams, which is the goal of this work. We proposed the utilization of a coupled 3D Convolutional Neural Network (CNN) architecture that can map both modalities into a representation space to evaluate the correspondence of audio-visual streams using the learned multimodal features. -
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Flow Teleprompter
A Windows first teleprompter with voice tracking and AI drafting.
Flow is a high performance desktop teleprompter built with Tauri and Rust. It is designed for creators who need a clean reading surface without sacrificing advanced features like native speech tracking and app wide voice commands. It features five playback styles including scroll and voice sync, local first privacy, and built in script editing. Version 1.6.1 introduces a rebuilt Vosk engine for faster recognition and significantly lower RAM usage. Whether you are using the Groq powered AI drafting or the remote messaging system to push scripts from another device, Flow stays lightweight and out of the way. Teleprompter. -
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NVIDIA NeMo
Toolkit for conversational AI
NVIDIA NeMo, part of the NVIDIA AI platform, is a toolkit for building new state-of-the-art conversational AI models. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI architectures are typically large and require a lot of data and compute for training. NeMo uses PyTorch Lightning for easy and performant multi-GPU/multi-node mixed-precision training. Supported models: Jasper, QuartzNet, CitriNet, Conformer-CTC, Conformer-Transducer, Squeezeformer-CTC, Squeezeformer-Transducer, ContextNet, LSTM-Transducer (RNNT), LSTM-CTC. NGC collection of pre-trained speech processing models. -
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Voxal voice changer
Transform your voice in real-time voxal voice changer
Voxal Voice Changer is a program that allows you to modify your voice by applying various effects (e.g. pitch change, echo, etc.) in real-time. Effects can be added in any sequence and in any combination, allowing you to distort your voice beyond recognition. Take your audio to the next level! Our powerful Voice Changer software lets you morph your voice in real-time with stunning AI-powered quality. Whether you're looking to have fun, protect your privacy, or create engaging content, we have the perfect voice for you. Audio can be captured from various sources, pre-listening is available, and the most popular audio formats are supported. -
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A speech synthesis and recognition library that is cross-platform, accessible from Java and C++, and has a very small API. Uses CMU Sphinx4 and FreeTTS internally.
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Polaris programing with voice in Eclipse
Polaris, programing with voice in Eclipse IDE
With Polaris you have the possibility of incorporating speech into programing. Through use of this plugin in Eclipse IDE you can see that not only is it possible to provide an environment for a programing with voice, but that programing with voice it is part of the natural evolution of programming tools. VOICE COMMANDS eclipse task eclipse search eclipse skip eclipse format eclipse new eclipse save eclipse rename eclipse cut eclipse copy eclipse paste eclipse all eclipse delete eclipse close eclipse get eclipse hash eclipse string Efforts are made on daily basic to increase the range of functionality that can be controlled with voice. PREREQUISITE Windows OS and Eclipse IDE. Headphones with microphone, not mandatory, but it will improve speech recognition. Port Number that is setted in Polaris Preference page must not be used by any other application. -
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JuliusModels
Open source speech models for Julius in English and other languages.
Open source speech models for Julius speech decoder. Its aim is to give access a wider community of speech recognition enthusiasts to quality models, which they can use in their own projects on different OS platforms (Unix, Windows, etc...) All of the models are based on HTK modelling software and data sets available freely on the Internet. -
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JAVT - Just Another Voice Transformer
Just Another Speech Recognition and Text to Speech software.
JAVT or Just Another Voice Transformer (formerly, it is called Just Another Video Transcriber) is a Speech Recognition software that also support text to Speech and simple media conversion. JAVT allows you to convert from video files to audio wav file using ffmpeg, and then transcribe the audio file to text using either Microsoft SAPI or CMU Sphinx. You can also open a text file and allow JAVT to read it out for you through text to speech conversion. -
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ILA - teachable voice assistant
ILA is a fully customizable and teachable voice assistant for Java
ILA stands for (kind of) intelligent, learning assistant and is a speech recognition system aka voice assistant very similar to Siri, Google Now and Cortana. ILA is fully customizable and you can teach her/him/it new things by yourself like executing system commands, opening web pages, programs and apps or just some basic conversation :-) ILA runs on Java und thus is compatible to Windows, Mac and Linux. It is designed to integrate with your home enviroment and for example build up your own, free and open Amazon Echo replacement ;-) Right now the key components of ILA are the open source speech recognition CMU Sphinx-4, Google (Speech Recognition/Text-To-Speech) and MaryTTS (Text-To-Speech). The goal is to make ILA completely free of Google by improving all aspects of the open source systems. Since version 3.3 users can also write own add-ons to extend ILA. ILA's successor is the SEPIA Framework: https://sepia-framework.github.io/ Hope you enjoy ILA - Florian -
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Open Pandora's Box
Pandora is an artificial intelligent web based bot
Pandora is an artificial intelligent web based bot written in Java. Pandora is a component based AI architecture including, database memory, XML, voice, voice rec, chat, IRC, HTTP, Wiktionary, Freebase, consciousness, language, GUI, applet, web, jsp, Android
