hearing.backends.whisperx.config

Configuration for the WhisperX backend.

WhisperX = batched faster-whisper + wav2vec2 forced alignment (accurate word timestamps) + optional pyannote speaker diarization, in one pass — the sweet spot for multi-speaker meetings.

Diarization is off by default (in hearing, speakers are a separate concern — see the hearing-diarization skill); pass diarize=True to have WhisperX label speakers. It needs a Hugging Face token (env HF_TOKEN) that has accepted the pyannote model terms. device/compute_type default to CUDA + float16 when a GPU is visible, else CPU + int8.

Module Attributes

DEFAULT_MODEL	Default Whisper model size for WhisperX.
HF_TOKEN_ENV_VARS	Env var(s) holding the Hugging Face token pyannote diarization needs.

hearing.backends.whisperx.config.DEFAULT_MODEL = 'large-v3'

Default Whisper model size for WhisperX.

hearing.backends.whisperx.config.HF_TOKEN_ENV_VARS = ('HF_TOKEN', 'HUGGING_FACE_HUB_TOKEN')

Env var(s) holding the Hugging Face token pyannote diarization needs.