sanchit-gandhi HF staff commited on
Commit
e9ece4c
1 Parent(s): 3218f45
.idea/.gitignore ADDED
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.idea/whisper-tiny.iml ADDED
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README.md CHANGED
@@ -351,7 +351,8 @@ This code snippet shows how to evaluate Whisper Tiny on [LibriSpeech test-clean]
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  The Whisper model is intrinsically designed to work on audio samples of up to 30s in duration. However, by using a chunking
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  algorithm, it can be used to transcribe audio samples of up to arbitrary length. This is possible through Transformers
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  [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
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- method, which can also be extended to predict utterance level timestamps:
 
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  ```python
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  >>> import torch
 
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  The Whisper model is intrinsically designed to work on audio samples of up to 30s in duration. However, by using a chunking
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  algorithm, it can be used to transcribe audio samples of up to arbitrary length. This is possible through Transformers
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  [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
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+ method. Chunking is enabled by setting `chunk_length_s=30` when instantiating the pipeline. It can also be extended to
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+ predict utterance level timestamps by passing `return_timestamps=True`:
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  ```python
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  >>> import torch