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Hi @tmbdev , thanks for your reply in #24, it is perfect!
I have another question and have commented in #24. Here I copy the question for easier retrieval for other people.
Can the predict interface provide top-N results? That will be helpful for better results and finding weakness of datasets.
Thanks.
The text was updated successfully, but these errors were encountered:
No, the predict interface does not give you top-N. To get top-N, you'd have to implement a beam decoder or some other decoder.
I'm planning on hooking up the OpenFST library to the CLSTM library. That gives you one simple option for top-N computations (plus a lot more).
Sorry, something went wrong.
Beam search implementations: https://github.com/amaas/stanford-ctc/search?l=cpp&q=beam&utf8=%E2%9C%93
https://github.com/search?l=cpp&q=%22beam+search%22+%22ctc%22&ref=searchresults&type=Code&utf8=%E2%9C%93
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Hi @tmbdev , thanks for your reply in #24, it is perfect!
I have another question and have commented in #24.
Here I copy the question for easier retrieval for other people.
Can the predict interface provide top-N results?
That will be helpful for better results and finding weakness of datasets.
Thanks.
The text was updated successfully, but these errors were encountered: