Search Results for "anpr using python"

...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. ...

PersonaPlex is an open-source real-time conversational speech AI model that goes beyond traditional text chat by providing full-duplex speech-to-speech interaction, meaning it can listen and talk at the same time instead of waiting for you to finish speaking before responding. This architectural approach eliminates awkward pauses and makes conversations feel much more human-like, with natural behaviors such as overlapping speech, interruptions, and fluent turn-taking, traits that traditional...

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...

Just log your favorite FM station speech to a text file using rtl-sdr dongle and speech recognition. Cross-platform tool. Follow the README on the download page for Windows installation. https://sourceforge.net/projects/fm2txt-rtlsdr/files/ If you prefer GitHub source, not SF: https://github.com/randaller/fm2txt For those, who want to recognize from soundcard, not from rtl-sdr (this allows to transcribe NFM etc): https://github.com/randaller/souncard2txt

Steel is a cross-platform package for using common text-to-speech (speech synthesis) engines in Python. Steel currently supports the following TTS software: - Microsoft Speech API 5 (SAPI5) - eSpeak - NS Speech Synthesis - FreeTTS Documentation: http://sourceforge.net/p/steeltts/wiki/ Bug Tracker: http://sourceforge.net/p/steeltts/tickets/ If you are interested in contributing to the Steel TTS codebase, or would like to make a feature-request, please contact the lead developer, Jasper Danielson, at jrd4@rice.edu.

Voice keyboard/dictation. Aims to be a total substitute for a keyboard. Spell out words letter by letter (using code: alpha, bravo, ..). Arrow keys, modifiers work. Speak whole words (but whole word accuracy is not good). Attach commands to some word

...Features: - logs into, and checks your gmail accounts - if you have unread email: - textual info about it appears in console/terminal - "you have X unread email" is spoken using espeak - if you have no unread email: - textual info about it appears in console/terminal Requirements: - POSIX OS - python: import imaplib import os import time - espeak - soundcard, speakers/headphones Installation/running: - modify gmail.py inserting your username and password - modify gmail.py inserting desired delay value in miliseconds - run: python gmail.py Author: pkrawczak@gmail.com 2013-02-06 13:54:51 Caution: Even though this program uses SSL use only at your own risk.

VEDICS (Voice Enabled Desktop Interaction and Control System) is an assistive software which lets the user to interact with the OS using voice commands. Using this software the user can access any element found on the user's screen.

ASR-Builder provides an easy-to-use interface to the HTK toolkit, that allows users to build ASR systems. ASR-Builder provides a platform that performs house-keeping tasks when using HTK and also provides default training/testing/recognition scripts.

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.