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fix a typoe #65

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abdelkareemkobo opened this issue Jun 24, 2023 · 1 comment
Open

fix a typoe #65

abdelkareemkobo opened this issue Jun 24, 2023 · 1 comment

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@abdelkareemkobo
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abdelkareemkobo commented Jun 24, 2023

In UNIT4 : Pretrained models for audio classification
We’ll load an official Audio Spectrogram Transformer checkpoint fine-tuned on the Speech Commands dataset, under the namespace "MIT/ast-finetuned-speech-commands-v2":

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classifier = pipeline(
"audio-classification", model="MIT/ast-finetuned-speech-commands-v2"
)
classifier(sample["audio"])
Fix it to be classifier(sample["audio"]["array"])
I don't know how to make a pull request yet! :)

@osamja
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osamja commented Jan 4, 2024

@abdelkareemkobo Hmm, I think we may need to be careful here. I just submitted a PR for a related fix. I initially thought that the following two statements were equivalent but they are not

Screenshot 2024-01-03 at 10 07 57 PM

The above is for the minds-14 dataset, not Speech Commands but in this case classifier(sample["audio"]) produces the correct intent classification whereas adding the "array" index does not. I'm currently not able to load the speech command dataset (it hangs when trying to stream the dataset in). What is the difference in output when trying to classify these two different ways on the Speech Commands dataset?

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