mixing.transcript.fillers

Filler-word detection over Scribe-shaped word lists.

A “word list” here is the words array in the ElevenLabs Scribe JSON response — each entry has text, start, end, and type (one of "word", "spacing", "audio_event").

The two main outputs are:

• build_cuts(): time ranges to REMOVE (fillers + optional audio events).

• keeps_from_cuts(): complementary KEEP ranges, suitable for ffmpeg.

Module Attributes

DEFAULT_FILLER_TOKENS	Default filler tokens (lowercased, alpha-only, see normalize_token()).
DEFAULT_AUDIO_EVENTS_TO_CUT	Default audio-event tags to remove.

Functions

build_cuts(words, *[, fillers, ...])	Compute time ranges to REMOVE.
is_filler(item, *[, fillers, audio_events])	Return True if item is a filler word or a removable audio event.
keeps_from_cuts(cuts, duration)	Return ranges to KEEP given the cut ranges and total duration.
normalize_token(text)	Lowercase and strip non-alpha so "Uh," -> "uh".

mixing.transcript.fillers.DEFAULT_AUDIO_EVENTS_TO_CUT: frozenset[str] = frozenset({'(coughs)'})

Default audio-event tags to remove. (laughs) is intentionally kept.

mixing.transcript.fillers.DEFAULT_FILLER_TOKENS: frozenset[str] = frozenset({'ah', 'eh', 'er', 'erm', 'hmm', 'mhm', 'mm', 'mmm', 'uh', 'uhh', 'uhm', 'um', 'umm'})

Default filler tokens (lowercased, alpha-only, see normalize_token()).

mixing.transcript.fillers.build_cuts(words, *, fillers=frozenset({'ah', 'eh', 'er', 'erm', 'hmm', 'mhm', 'mm', 'mmm', 'uh', 'uhh', 'uhm', 'um', 'umm'}), audio_events=frozenset({'(coughs)'}), absorb_trailing_space=True, merge_gap=0.08)

Compute time ranges to REMOVE.

Parameters:

• words (Sequence[dict]) – Scribe words array.

• fillers (Iterable[str]) – Override the default filler set.

• audio_events (Iterable[str]) – Override the default audio-event set.

• absorb_trailing_space (bool) – Extend each cut to the end of the trailing "spacing" token, which avoids leaving a stranded pause.

• merge_gap (float) – Merge adjacent cuts when their gap is below this many seconds.

Return type:

list[dict]

Returns:

List of {"start": float, "end": float, "label": str} dicts, sorted by start time and non-overlapping.

mixing.transcript.fillers.is_filler(item, *, fillers=frozenset({'ah', 'eh', 'er', 'erm', 'hmm', 'mhm', 'mm', 'mmm', 'uh', 'uhh', 'uhm', 'um', 'umm'}), audio_events=frozenset({'(coughs)'}))

Return True if item is a filler word or a removable audio event.

Return type:

bool

mixing.transcript.fillers.keeps_from_cuts(cuts, duration)

Return ranges to KEEP given the cut ranges and total duration.

Return type:

list[dict]

mixing.transcript.fillers.normalize_token(text)

Lowercase and strip non-alpha so "Uh," -> "uh".

Return type:

str