Things to Look Into
OpenAI Whisper delivers highly accurate speech-to-text transcription, but it does not track speaker changes. Applications that rely on Whisper cannot determine who is speaking in a conversation. To add speaker labels such as "Speaker 1" and "Speaker 2," you can integrate Falcon Speaker Diarization with whisper.cpp. creating a fully local, offline, multi-speaker transcription system.
This tutorial explains how to add speaker segmentation to Whisper, so you can determine "who spoke when" and generate timestamps to produce labeled Whisper transcripts suitable for multi-speaker recordings. This approach is ideal for use cases such as podcast transcriptions, meeting transcription and summarization, or call center analytics, where speaker identification is essential for readability and downstream analysis.
Arbeitet wohl nicht mit whisper.cpp zusammen? Sonst wäre es einen Blick wert.
Harbor is a CLI and companion app that lets you spin up a complete local LLM stack—backends like Ollama, llama.cpp, or vLLM, frontends like Open WebUI, plus supporting services like SearXNG for web search, Speaches for voice chat, and ComfyUI for image generation—all pre-wired to work together with a single
harbor upcommand. No manual setup: just pick the services you want and Harbor handles the Docker Compose orchestration, configuration, and cross-service connectivity so you can focus on actually using your models.