Popular GitHub Repositories for Mems Microphone

Alias is a teachable “parasite” that is designed to give users more control over their smart assistants, both when it comes to customisation and privacy. Through a simple app the user can train Alias to react on a custom wake-word/sound, and once trained, Alias can take control over your home assistant by activating it for you.

Real-time voice-changer for voice-chat, etc. Will support many different voice-filters and features in the future. ?

Project that allows one to use a microphone with OpenAI whisper.

The J.A.R.V.I.S. Speech API is designed to be simple and efficient, using the speech engines created by Google to provide functionality for parts of the API. Essentially, it is an API written in Java, including a recognizer, synthesizer, and a microphone capture utility. The project uses Google services for the synthesizer and recognizer. While this requires an Internet connection, it provides a complete, modern, and fully functional speech API in Java.

Mimic Recording Studio is a Docker-based application you can install to record voice samples, which can then be trained into a TTS voice with Mimic2

The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.

Transcribe is a real time transcription, conversation, Language learning platform. It provides live transcripts from microphone and speaker. It generates a suggested conversation response using OpenAI's GPT API. It will read out the responses, simulating a real live conversation in English or another language.

Fully local, no dependency scribe. Speak into your microphone and summarize. Requires iOS 26 and MacOS 26 to use the advanced transcription model and foundational model for summaries

A desktop application that transcribes audio from files, microphone input or YouTube videos with the option to translate the content and create subtitles.

The Official PyTorch Implementation of FN-SSL & IPDnet for Sound Source Localization [INTERSPEECH2023 & TASLP2024]

In this project is presented a simple method to train an MLP neural network for audio signals. The trained model can be exported on a Raspberry Pi (2 or superior suggested) to classify audio signal registered with USB microphone

A proof of concept text-to-speech application allowing global typing. Can be used over applications such as voice chats, games and much more.

This chatbot lets you use your microphone to communicate with GPT-4. It uses the OpenAI text to speech to respond with a voice. It uses Pinecone to store long term information and retrieves it to create context. API keys for OpenAI and Pinecone required. Tested on Windows

Demo python script app to interact with llama.cpp server using whisper API, microphone and webcam devices.

Live translator that captures any audio that comes from a WINDOWS speaker or microphone and translates it to the desired language.

Your speech assistant. Communicate with text-to-speech in games, on voice chat, on stream or simply on your speakers!

A repository for my MSc thesis in Data Science & Machine Learning @ NTUA. A deep learning approach to audio fingerprinting for recognizing songs on real time through the microphone.

? Transcribe input from your microphone and turn it into key presses on a virtual keyboard. ⌨️ This allows you to use speech-to-text on any application or window system in Linux. In fact, you can use it on the system console.

stm32-speech-recognition-and-traduction is a project developed for the Advances in Operating Systems exam at the University of Milan (academic year 2020-2021). It implements a speech recognition and speech-to-text translation system using a pre-trained machine learning model running on the stm32f407vg microcontroller.

A python implementation of “Self-Supervised Learning of Spatial Acoustic Representation with Cross-Channel Signal Reconstruction and Multi-Channel Conformer” [TASLP 2024]