Open Source Python Speech to Text Software

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.

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. If you want to use the pre-trained English model for performing speech-to-text, you can download it (along with other important inference material) from the DeepSpeech releases page.

Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using pip install SpeechRecognition. The first software requirement is Python 2.6, 2.7, or Python 3.3+. This is required to use the library. PyAudio is required if and only if you want to use microphone input (Microphone). PyAudio version 0.2.11+ is required, as earlier versions have known memory management bugs when recording from microphones in certain situations. To hack on this library, first make sure you have all the requirements listed in the "Requirements" section.

RealtimeSTT is a Python-based realtime speech-to-text engine emphasizing low latency, wake-word detection, voice activity detection, and automatic speech segmentation. It provides asynchronous callbacks, nanosecond-precision timestamps, and CLI tools, suitable for building voice assistants, meeting transcribers, or live caption systems.

SoundTranscriber can be used to generate automatic transcription / aut

It generates srt format subtitle from videofile which can be any source language that whisper support , and then make translated subtitle file of your target language which deepl support. This is the subtitle generator(VATSG) which use [moviepy](https://github.com/Zulko/moviepy) to generate mp3 and then use [faster-whisper](https://github.com/guillaumekln/faster-whisper) to get text recognition and then use deepl-api to generate your target language subtitle file(srt format) If you are a general user who want to view any video file and mp3 file to your language, It will provide way. It's very easy to use because it has simple gui and very intuitive. So you can easily use it for any purpose. Now, you can choose to download either window installer setup type or uninstalled type. Enjoy and support my consistent development!

## About: Automatically transcribe all of your voice recordings into clean, organized, neat text files. It's free, fully automated, unlimited, using state-of-the-art speech-to-text technology. Works 100% offline on your computer, privately and locally. ## Usecases: Convert speeches, podcasts, webinars, monologues, storytellings and other audio speech into a formatted .txt file. One sentence per new line. ## Notes: - Its 2GB in size and requires 2-6GB of GPU VRAM too. (basically you need atleast a mid-range gaming PC to use this.) - Its fairly slow to start (10min) and transcribe, this is normal behavior. - Includes a python installer to install Python on your computer so you can directly run the 'whisper_transcriber.py' file like you would an .exe by double-clicking it. (I did this because compiling to exe made it slower) - I made it as easy as possible for a layperson to use, so despite its crude looks, its as good as a GUI application experience. Enjoy freedom!

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.

Note about this image This image contains a system based on Linux MX, which was created to improve accessibility within the Linux environment. The distribution uses the Cinnamon desktop interface, which is configured to be operated using voice commands and outputs. The user interface and the control of your own devices and home automation systems can be customized and extended. The voice control program MiceStTM.py was developed to enable easy adaptation to other languages. However, only German settings are currently implemented. category: System commands comment: Screen grid trigger: Display screen (Ras.*|Grid)* terminal_command: /opt/micesttm/read-aloud/screen_grid.py & sleep 1 && xdotool search --name "screen grid" windowactivate intern_command: tts: Screen grid for the mouse click was selected.

Voice Conference Manager uses VoiceXML and CCXML to control speech recognition, text to speech, and voice biometrics for a telephone conference service. Say the names or numbers of people and VCM places them into the call. Can be hosted on public servers

An async Python library to automate solving ReCAPTCHA v2 by images/audio using Mozilla's DeepSpeech, PocketSphinx, Microsoft Azure’s, Google Speech and Amazon's Transcribe Speech-to-Text API. Also image recognition to detect the object suggested in the captcha. Built with Pyppeteer for Chrome automation framework and similarities to Puppeteer, PyDub for easily converting MP3 files into WAV, aiohttp for async minimalistic web-server, and Python’s built-in AsyncIO for convenience.

Dieses Tool wird speziell für die Barrierefreiheit unter Linux entwickelt. Es ermöglicht das umwandeln/konvertieren/parsen von Texten die aus einer Spracherkennung stammen, in Diktate sowie das Ausführen von Makros. Dies funktioniert ohne Internet, da die Spracherkennung auf dem PC selbst erfolgt. Mausbewegungen auf benannte Wörter und dann entsprechend auswählen oder per Sprachbefehl klicken. Außerdem können Textpassagen z.B. unter Libreoffice Wirter per Sprachbefehl entsprechend ausgewählt und bearbeitet werden. Springe zum Satzende und so weiter. Hausautomatisierungen können realiesiert werden. Nach jedem Befehl kann ein Feedback per Sprachausgabe erfolgen.(tts) Makros können das Licht einschalten oder den Fernseher per Broadlink steuern. Je nach dem welche Idee man hat.

Software to fit whole-sentence language models using the principle of maximum entropy. For developers of speech recognizers, text prediction interfaces, OCR, machine translation software.