LPCNet | Experimental Neural Net speech coding for FreeDV | Machine Learning library

by drowe67 C Version: v0.3 License: BSD-3-Clause

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | LPCNet Summary

LPCNet is a C library typically used in Artificial Intelligence, Machine Learning applications. LPCNet has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Experimental version of LPCNet that has been used to develop FreeDV 2020 - a HF radio Digital Voice mode for over the air experimentation with Neural Net speech coding. Possibly the first use of Neural Net speech coding in real world operation.

Support

Quality

Security

License

Reuse

Support

LPCNet has a low active ecosystem.

It has 65 star(s) with 19 fork(s). There are 13 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 14 have been closed. On average issues are closed in 187 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of LPCNet is v0.3

Quality

LPCNet has 0 bugs and 0 code smells.

Security

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

LPCNet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

LPCNet is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

LPCNet releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

It has 662 lines of code, 29 functions and 9 files.

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

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LPCNet Key Features

No Key Features are available at this moment for LPCNet.

LPCNet Examples and Code Snippets

LPCNet for FreeDV,Quickstart

Lines of Code : 10

License : Permissive (BSD-3-Clause)

Copy

$ git clone https://github.com/drowe67/codec2.git
$ cd codec2 && mkdir build_linux && cd build_linux && cmake ../ && make
$ cd ~
$ git clone https://github.com/drowe67/LPCNet.git
$ cd LPCNet && mkdir build_linu

Quantiser Experiments,Exploring Features

Lines of Code : 6

License : Permissive (BSD-3-Clause)

Copy

$ ./dump_data --test speech_orig_16k.s16 speech_orig_16k_features.f32
$ cd src
$ octave --no-gui
octave:3> f=load_f32("../speech_orig_16k_features.f32",55);
nrows: 1080
octave:4> mesh(f(1:100,1:18))

Quantiser Experiments,Training a Predictive VQ

Lines of Code : 5

License : Permissive (BSD-3-Clause)

Copy

$ git clone https://github.com/drowe67/codec2.git
$ cd codec2 && mkdir build_linux && cd build_linux && cmake ../ && sudo make install

$ cd LPCNet
$ ./dump_data --train all_speech.s16 all_speech_features_5e6.f32 /dev/

Community Discussions

Trending Discussions on LPCNet

Is it possible to use Keras module in Pytorch script?

QUESTION

Is it possible to use Keras module in Pytorch script?

Asked 2019-May-23 at 08:27

I'm creating a network similar to lpcnet introduced by mozilla but in PyTorch. At the one point I need the module src/mdense.py in my script but it is written with keras. Is it possible to import keras module to torch framework? What could be the easiest way? I don't want to re-write the module with PyTorch.

There exists some converters but as I see, these are in early stages. Is there any I can depend on?

...

ANSWER

Answered 2019-May-23 at 08:22

No, not really, you can import it (as in python import), but Keras code won't work with PyTorch as they use different differentiation methods and they are completely different libraries. The only way is to rewrite the module using PyTorch's API.

Source https://stackoverflow.com/questions/56270834

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

Vulnerabilities

No vulnerabilities reported

Install LPCNet

LPCNet at 1733 bits/s using direct-split quantiser:.

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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