speech-transformer | Transformer framework speciaized in speech recognition | Speech library

by sooftware Python Version: v1.0 License: MIT

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

kandi X-RAY | speech-transformer Summary

speech-transformer is a Python library typically used in Artificial Intelligence, Speech, Deep Learning, Pytorch, Transformer applications. speech-transformer has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However speech-transformer build file is not available. You can download it from GitHub.

Transformer framework speciaized in speech recognition tasks using Pytorch.

Support

Quality

Security

License

Reuse

Support

speech-transformer has a low active ecosystem.

It has 26 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of speech-transformer is v1.0

Quality

speech-transformer has no bugs reported.

Security

speech-transformer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

speech-transformer is licensed under the MIT License. This license is Permissive.

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

Reuse

speech-transformer releases are available to install and integrate.

speech-transformer has no build file. You will be need to create the build yourself to build the component from source.

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

Top functions reviewed by kandi - BETA

kandi has reviewed speech-transformer and discovered the below as its top functions. This is intended to give you an instant insight into speech-transformer implemented functionality, and help decide if they suit your requirements.

Performs the forward computation
Calculate successor
Performs a forward step
Get the non - padding mask
Returns a list of the predicted sentences
Takes a sequence of y_hats
Given a sequence of attn
Returns True if all tasks are finished
Inflate tensor
Forward computation

Get all kandi verified functions for this library.

speech-transformer Key Features

No Key Features are available at this moment for speech-transformer.

speech-transformer Examples and Code Snippets

No Code Snippets are available at this moment for speech-transformer.

Community Discussions

Trending Discussions on speech-transformer

What is attention penalty in speech transformer paper? (updated)

QUESTION

What is attention penalty in speech transformer paper? (updated)

Asked 2020-Jan-13 at 15:13

github: https://github.com/sephiroce/tfsr/tree/exprimental

I'm trying to reproduce recognition accuracies described in the speech transformer paper [1]. The attention penalty is a technique I could not fully understand. This is the description of the attention penalty in the paper.

"In addition, we encouraged the model attending to closer positions by adding bigger penalty on the attention weights of more distant position-pairs."

I understood as it means adding smaller negative values for more away from the diagonal on scaled attention logits (before masking) except for the first multi-head attention in decoders.

This is a code snippet for computing attention weights.

...

ANSWER

Answered 2020-Jan-13 at 10:33

I think you understand it well. They probably did a stripe around the diagonal, something like:

Source https://stackoverflow.com/questions/59646954

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

Vulnerabilities

No vulnerabilities reported

Install speech-transformer

You can download it from GitHub.
You can use speech-transformer like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

If you have any questions, bug reports, and feature requests, please open an issue on github or contacts sh951011@gmail.com please. I appreciate any kind of feedback or contribution. Feel free to proceed with small issues like bug fixes, documentation improvement. For major contributions and new features, please discuss with the collaborators in corresponding issues.

Find more information at: