Fully automated multi-speaker transcription tool built off of the WhisperX library with Pyannote. Comes with Word Alignment, Timestamps, Voice activity Detection and Speaker Diarization. Mathematically optimised for accuracy.

Python implementation of the NIST md-eval.pl script for evaluating rich transcription and speaker diarization accuracy.

An English-Spanish code switching dataset adapted from the Miami-Corpus

A Python CLI tool for transcribing podcasts with automatic speaker diarisation using OpenAI's Whisper API. Features real-time progress tracking, cost estimation, automatic chunking for large files, and clean Markdown output with timestamps. Supports both URLs and local files. Python 3.10+ compatible.

Voice-bank-first speaker labelling for the Plaud Note family. Local, macOS Apple Silicon, AGPL-3.0.