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whisperx-tiny
WhisperX Tiny is a fast and accurate speech recognition model with speaker diarization capabilities. Built on OpenAI's Whisper with additional features for alignment and speaker segmentation.

Repository: localaiLicense: mit

vibevoice-cpp-asr
VibeVoice ASR 7B (C++ / GGML, Q4_K) - long-form speech-to-text with speaker diarization. Returns per-speaker JSON segments with start/end timestamps. English-only. ~10 GB download.

Repository: localaiLicense: mit

moss-transcribe-cpp-0.9b
MOSS-Transcribe-Diarize 0.9B, an end-to-end audio understanding model for joint multi-speaker transcription, speaker diarization and timestamping in a single pass. Q5_K GGUF for the moss-transcribe-cpp backend (C++/ggml port of OpenMOSS MOSS-Transcribe-Diarize), byte-identical to the reference at ~1/6 the size. Faster than the reference PyTorch runtime on CPU (1.6 to 2.2x).

Repository: localaiLicense: apache-2.0

audio-cpp-sortformer-diarization
Sortformer Diarization 4-speaker v1 (audio.cpp, Q8_0) - speaker diarization for up to four speakers, served by the audio-cpp backend through /v1/audio/diarization. Returns per-segment start, end and speaker label; it does not transcribe, so pair it with an ASR model for text. Q8_0 because upstream records it as a clean Pass, the same as 16-bit, at two thirds of the size. Licensing: the base checkpoint nvidia/diar_sortformer_4spk-v1 is CC BY-NC 4.0, so commercial use is not permitted.

Repository: localaiLicense: cc-by-nc-4.0