Search Results for "showeq open source project"

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...

WhisperKit is a Swift package that integrates OpenAI's popular Whisper speech recognition model with Apple's CoreML framework for efficient, local inference on Apple devices. Whisper has pulled the future forward when fast, free and virtually error-free translation and transcription will be ubiquitous. It inspired numerous developers to improve and deploy it with minimal friction and maximum performance. We founded Argmax in November 2023 to empower developers and enterprises everywhere to...

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...

Omnilingual-ASR is a research codebase exploring automatic speech recognition that generalizes across a very large number of languages using shared modeling and training recipes. It focuses on leveraging self-supervised audio pretraining and scalable fine-tuning so low-resource languages can benefit from high-resource data. The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new...

This project provide hidden Markov model speech recognition system by using Matlab/Simulink/Stateflow.

This project is being developed to be a Java based speech recognition (SR) program. In addition to the SR program itself, it includes a program which allows a user to view the sound being received by the computer. The user can manipulate this data.

Project aim to provide simple easy APIs for Java developers to use interactive abilities in their Java Applications like speech recognition, handwriting recognition, use of web cam , sound record/play, decision trees , text to speech and many others.

This project, npp (net plus plus, net++), is developed on top of open source package QuickNet for Neural Network training in speech recognition.

This project will show how to implement the Hidden Markov Model approximations of Voice Recognition into embedded and low power systems.

The aim of this project is to develop a software to assist speech recognition systems users by displaying outputs of their systems.