Very fast, accurate speaker diarization

The Package Manager for the Swift Programming Language

Superwhisper is an AI voice-to-text tool for quick and accurate transcription. Download free now.

State-of-the-art TTS model under 25MB 😻

Apple and Android Device Knowledge Base for On-device Inference Deployment Configurations

Argmax SDK Swift Playground

Local-first AI Notepad for Private Meetings

Voice-to-text app for macOS to transcribe what you say to text almost instantly

VOICE → WORDS

A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

The simplest, fastest repository for training/finetuning small-sized VLMs.

This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025

An implementation of the Nvidia's Parakeet models for Apple Silicon using MLX.

LiteRT continues the legacy of TensorFlow Lite as the trusted, high-performance runtime for on-device AI. Now with LiteRT Next, we're expanding our vision with a new generation of APIs designed for…

Open-source reproducible benchmarks from Argmax

A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.

Towards Human-Sounding Speech

SmolVLM2 Demo

The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.

Pipelines for running pretrained Core ML models

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

Python tools for WhisperKit: Model conversion, optimization and evaluation

Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/

Example PIR service & documentation for Live Caller ID Lookup & NEURLFilter

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

The Qualcomm® AI Hub apps are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.