Comments (3)
aaronzira
commented on May 24, 2024
Nevermind, I think I found the obvious thing I was missing -- my LM is trained on lowercased words, and my deepspeech output is uppercased =X My first question remains, though, as to the expected sizes and contents of the trie files.
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Diamondfan
commented on May 24, 2024
I have the same problem. There seems few usage about generate_lm_trie. I get the same CER and WER with beam search decoder.
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SeanNaren
commented on May 24, 2024
This should be fixed now, reducing the OOV weight makes the LM stronger in #22 . I'd also suggest increasing the alpha parameter from the default incrementally to see better LM results!
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Related Issues (20)
- problem with CTCBeamDecoder.decode() when using a big (.arpa / .binary) file HOT 1
- I can't dockerize my project with ctcdecode library HOT 1
- "Symbol not found in flat name space" in MacOS (macbook pro M1) when importing ctcdecode HOT 1
- pip install error on Linux HOT 2
- out_len and out_lens
- Calculation of "beam_scores" and gradient HOT 2
- probelm on installing ctcdecode in window
- probelm when installing ctcdecode in window HOT 1
- You can migrate your code to kaggle, install the package through kaggle. See the website below for installation.
- RuntimeError: Resource temporarily unavailable
- could the ctcdecode be serialized and executed in non-Python environments, such as torchscript?
- #error C++17 or later compatible compiler is required to use PyTorch
- pip install . errro on colab HOT 3
- Unable to run the pip install . command HOT 1
- How to use timesteps information to calculate word-level alignments? HOT 2
- Can you list the dependencies like torch version, c++ and others HOT 1
- PIP install issue Windows HOT 1
- Can we just update this repo HOT 1
- Share how to install successful "ctcdecode" HOT 5
- beam scores of shape (batch, num_beams, time_steps)
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