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
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.
Voice-bank-first speaker labelling for the Plaud Note family. Local, macOS Apple Silicon, AGPL-3.0.
Transcription audio LOCAL M4A avec diarisation des locuteurs - Solution utilisant faster-whisper et clustering MFCC
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.
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