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Prevent timestamps restoration when clip timestamps are provided in batched inference (#1376)

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This commit is contained in:
Mahmoud Ashraf
2025-10-31 14:26:17 +03:00
committed by GitHub
parent 00a5b26b1f
commit 409a6919f9
2 changed files with 40 additions and 3 deletions
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20
faster_whisper/transcribe.py
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@@ -418,23 +418,34 @@ class BatchedInferencePipeline:
"Set 'vad_filter' to True or provide 'clip_timestamps'."
)
clip_timestamps_provided = False
audio_chunks, chunks_metadata = collect_chunks(
audio, clip_timestamps, max_duration=chunk_length
)
else:
clip_timestamps_provided = True
clip_timestamps = [
{k: int(v * sampling_rate) for k, v in segment.items()}
for segment in clip_timestamps
]
audio_chunks, chunks_metadata = [], []
for clip in clip_timestamps:
for i, clip in enumerate(clip_timestamps):
audio_chunks.append(audio[clip["start"] : clip["end"]])
clip_duration = (clip["end"] - clip["start"]) / sampling_rate
if clip_duration > 30:
self.model.logger.warning(
"Segment %d is longer than 30 seconds, "
"only the first 30 seconds will be transcribed",
i,
)
chunks_metadata.append(
{
"offset": clip["start"] / sampling_rate,
"duration": (clip["end"] - clip["start"]) / sampling_rate,
"duration": clip_duration,
"segments": [clip],
}
)
@@ -559,7 +570,10 @@ class BatchedInferencePipeline:
options,
log_progress,
)
segments = restore_speech_timestamps(segments, clip_timestamps, sampling_rate)
if not clip_timestamps_provided:
segments = restore_speech_timestamps(
segments, clip_timestamps, sampling_rate
)
return segments, info

23
tests/test_transcribe.py
View File

@@ -290,3 +290,26 @@ def test_cliptimestamps_segments(jfk_path):
" And so my fellow Americans ask not what your country can do for you, "
"ask what you can do for your country."
)
def test_cliptimestamps_timings(physcisworks_path):
model = WhisperModel("tiny")
pipeline = BatchedInferencePipeline(model=model)
audio = decode_audio(physcisworks_path)
clip_timestamps = [{"start": 0.0, "end": 5.0}, {"start": 6.0, "end": 15.0}]
transcripts = [
" Now I want to return to the conservation of mechanical energy.",
(
" I have here a pendulum. I have an object that weighs 15 kilograms"
" and I can lift it up one meter, which I have done now."
),
]
segments, info = pipeline.transcribe(audio, clip_timestamps=clip_timestamps)
segments = list(segments)
assert len(segments) == 2
for segment, clip, transcript in zip(segments, clip_timestamps, transcripts):
assert clip["start"] == segment.start
assert clip["end"] == segment.end
assert segment.text == transcript