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黑墨水鱼
2024-09-12 00:49:31 +08:00
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@@ -69,6 +69,7 @@ segments, info = model.transcribe("audio.mp3", beam_size=5, language="en")
* Python 3.8 or greater
Unlike openai-whisper, FFmpeg does **not** need to be installed on the system. The audio is decoded with the Python library [PyAV](https://github.com/PyAV-Org/PyAV) which bundles the FFmpeg libraries in its package.
### GPU
@@ -165,35 +166,6 @@ for segment in segments:
segments, _ = model.transcribe("audio.mp3")
segments = list(segments) # The transcription will actually run here.
```
### multi-segment language detection
To directly use the model for improved language detection, the following code snippet can be used:
```python
from faster_whisper import WhisperModel
model = WhisperModel("medium", device="cuda", compute_type="float16")
language_info = model.detect_language_multi_segment("audio.mp3")
```
### Batched faster-whisper
The batched version of faster-whisper is inspired by [whisper-x](https://github.com/m-bain/whisperX) licensed under the BSD-2 Clause license and integrates its VAD model to this library. We modify this implementation and also replaced the feature extraction with a faster torch-based implementation. Batched version improves the speed upto 10-12x compared to openAI implementation and 3-4x compared to the sequential faster_whisper version. It works by transcribing semantically meaningful audio chunks as batches leading to faster inference.
The following code snippet illustrates how to run inference with batched version on an example audio file. Please also refer to the test scripts of batched faster whisper.
```python
from faster_whisper import WhisperModel, BatchedInferencePipeline
model = WhisperModel("medium", device="cuda", compute_type="float16")
batched_model = BatchedInferencePipeline(model=model)
segments, info = batched_model.transcribe("audio.mp3", batch_size=16)
for segment in segments:
print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
```
### Faster Distil-Whisper
The Distil-Whisper checkpoints are compatible with the Faster-Whisper package. In particular, the latest [distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3)