kenlm | KenLM : Faster and Smaller Language Model Queries

by kpu C++ Version: windows License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(7)Vulnerabilities Install Support

kandi X-RAY | kenlm Summary

kenlm is a C++ library. kenlm has no bugs, it has no vulnerabilities and it has medium support. However kenlm has a Non-SPDX License. You can download it from GitHub.

Language model inference code by Kenneth Heafield (kenlm at kheafield.com). The website has more documentation. If you're a decoder developer, please download the latest version from there instead of copying from another decoder.

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kenlm has a medium active ecosystem.

It has 2166 star(s) with 477 fork(s). There are 68 watchers for this library.

It had no major release in the last 6 months.

There are 103 open issues and 251 have been closed. On average issues are closed in 167 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of kenlm is windows

Quality

kenlm has 0 bugs and 0 code smells.

Security

kenlm has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

kenlm code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kenlm has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

kenlm releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

It has 76 lines of code, 2 functions and 2 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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kenlm Key Features

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kenlm Examples and Code Snippets

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Community Discussions

Trending Discussions on kenlm

Subprocess call error while calling generate_lm.py of DeepSpeech

(0) Invalid argument: Not enough time for target transition sequence (required: 28, available: 24) During the Training in Mozilla Deepspeech

['kenlm/build/bin/build_binary', '-a', '255', '-q', '8', '-v', 'trie', 'lm_filtered.arpa', '/content/lm.binary']' returned non-zero exit status 1

DeepSpeech failed to learn Persian language

Set up kenlm for Windows

TypeError:__init__() missing 2 required positional arguments

Train DeepSpeech on Common Voice dataset gives error on gpu

QUESTION

Subprocess call error while calling generate_lm.py of DeepSpeech

Asked 2021-Dec-06 at 03:33

I am trying to build customised scorer (language model) for speech-to-text using DeepSpeech in colab. While calling generate_lm.py getting this error:

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ANSWER

Answered 2021-Dec-06 at 03:33

Able to find a solution for the above question. Successfully created language model after reducing the value of top_k to 15000. My phrases file has about 42000 entries only. We have to adjust top_k value based on the number of phrases in our collection. top_k parameter says - this much of less frequent phrases will be removed before processing.

Source https://stackoverflow.com/questions/70043586

QUESTION

(0) Invalid argument: Not enough time for target transition sequence (required: 28, available: 24) During the Training in Mozilla Deepspeech

Asked 2021-Sep-25 at 18:12

I am using below command to start the training of deepspeech model

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ANSWER

Answered 2021-Sep-25 at 18:12

Following worked for me

Go to

Source https://stackoverflow.com/questions/69328818

QUESTION

['kenlm/build/bin/build_binary', '-a', '255', '-q', '8', '-v', 'trie', 'lm_filtered.arpa', '/content/lm.binary']' returned non-zero exit status 1

Asked 2021-Sep-25 at 14:09

During the build of lm binay to create scorer doe deepspeech model I was getting the following error again and again

...

ANSWER

Answered 2021-Sep-25 at 14:09

Following worked for me Go to

Source https://stackoverflow.com/questions/69326923

QUESTION

DeepSpeech failed to learn Persian language

Asked 2021-May-15 at 08:12

I’m training DeepSpeech from scratch (without checkpoint) with a language model generated using KenLM as stated in its doc. The dataset is a Common Voice dataset for Persian language.

My configurations are as follows:

Batch size = 2 (due to cuda OOM)
Learning rate = 0.0001
Num. neurons = 2048
Num. epochs = 50
Train set size = 7500
Test and Dev sets size = 5000
dropout for layers 1 to 5 = 0.2 (also 0.4 is experimented, same results)

Train and val losses decreases through the training process but after a few epochs val loss does not decrease anymore. Train loss is about 18 and val loss is about 40.

The predictions are all empty strings at the end of the process. Any ideas how to improve the model?

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ANSWER

Answered 2021-May-11 at 14:02

maybe you need to decrease learning rate or use a learning rate scheduler.

Source https://stackoverflow.com/questions/67347479

QUESTION

Set up kenlm for Windows

Asked 2021-May-07 at 13:54

The official website makes it pretty clear that there is no support for kenlm in Windows. There is a Windows tag at the github repository but it seems to be maintained by few random contributors then and there.

How to set up kenlm for Windows then?

...

ANSWER

Answered 2021-Feb-27 at 16:08

The solution is to use Ubuntu in Windows through Windows Subsystem for Linux

Get WSL for Windows
From your ubuntu bash navigate to the folder where you want to do the setup. You can access the Windows file system from the /mnt/c/ folder, which you can find at the root directory.
From there simply follow the official instructions, that is clone the git repo, and run cmake .. & make -j2 in order to build the project (after first making the necessary installations in your Ubuntu system).

Obviously, you must train the models or scorers using the Linux bash. You can also use these models from Windows using the kenlm python library.

E.g.

The two steps to build a scorer for the deepspeech-model as described here should be executed from your Ubuntu system. But after you have the scorer you should be able to run the command

deepspeech --model deepspeech-0.9.3-models.pbmm --scorer kenlm.scorer --audio audio.wav

from Windows. However, once you have WSL there's no need to do this work from Windows. Things will work nicely @your Ubuntu system.

Source https://stackoverflow.com/questions/66400723

QUESTION

TypeError:__init__() missing 2 required positional arguments

Asked 2021-May-03 at 10:11

I am currently running into this error. I don't know what this error is caused by because I've declared the positional arguments path2 and path3 already in my code but the error says that this two arguments missing.

Error Message:TypeError: __init__() missing 2 required positional arguments: 'path2' and 'path3'

This is my code:

...

ANSWER

Answered 2021-May-03 at 09:47

You need to pass these parameters when calling an object of class Corpus.
corpus = Corpus(path, path2, path3, order=3)

Source https://stackoverflow.com/questions/67366751

QUESTION

Train DeepSpeech on Common Voice dataset gives error on gpu

Asked 2021-Apr-27 at 08:15

I'm trying to train DeepSpeech model on Common Voice dataset as it's stated in documentation. But it gives the following error:

...

ANSWER

Answered 2021-Apr-24 at 00:53

I've seen a similar error posted on the DeepSpeech Discourse and the issue there was the CUDA installation.

What is the value of your $LD_LIBRARY_PATH environment variable?

You can find this by doing:

Source https://stackoverflow.com/questions/67198198

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install kenlm

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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