sbrt2017 | end speech recognizer | Speech library

by igormq Python Version: Current License: MIT

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

kandi X-RAY | sbrt2017 Summary

sbrt2017 is a Python library typically used in Artificial Intelligence, Speech, Deep Learning applications. sbrt2017 has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However sbrt2017 build file is not available. You can download it from GitHub.

Towards an end-to-end speech recognizer for Portuguese using deep neural networks

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Quality

Security

License

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Support

sbrt2017 has a low active ecosystem.

It has 23 star(s) with 3 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 3 have been closed. On average issues are closed in 60 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of sbrt2017 is current.

Quality

sbrt2017 has 0 bugs and 0 code smells.

Security

sbrt2017 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

sbrt2017 code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

sbrt2017 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

sbrt2017 releases are not available. You will need to build from source code and install.

sbrt2017 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.

sbrt2017 saves you 598 person hours of effort in developing the same functionality from scratch.

It has 1393 lines of code, 117 functions and 19 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed sbrt2017 and discovered the below as its top functions. This is intended to give you an instant insight into sbrt2017 implemented functionality, and help decide if they suit your requirements.

Write the dataset to an hdf5 file
Convert the file to a list
Return whether the given label is a valid label
Check if text is valid
Returns the next iteration
Make inputs from inputs
Create a sparse matrix out of labels
Create inputs and labels
Load a keras model
Load meta data from an hdf5 file
Get all custom objects
Create a flow from a file
Create a flow from an hdf5 group
Construct a flow from a JSON file
Deframes a numpy array of frames
Round a number to the nearest half - up
Parse a list of values
Update the dictionary with the given values
Write the object to a JSON file
Load meta data from a file
Setup GPU
Calculate the log powspec
Compute filterbanks
Compute the MFCC of a given signal
Calculate the filterbanks for a given signal
Builds an LSTM
Updates the dictionary with the given values

Get all kandi verified functions for this library.

sbrt2017 Key Features

No Key Features are available at this moment for sbrt2017.

sbrt2017 Examples and Code Snippets

No Code Snippets are available at this moment for sbrt2017.

Community Discussions

Trending Discussions on sbrt2017

error on import preprocessing python library

QUESTION

error on import preprocessing python library

Asked 2018-Jul-16 at 16:04

The actual code is just importing preprocessing, what am i doing wrong here? How can i fix this? I am using code from github repo: sbrt2017

...

ANSWER

Answered 2018-Jul-16 at 16:04

on line 847 of memory.py on the joblib package i had a warning.warn that was expecting a string but got a DeprecationWarning instead and it blowed up

Source https://stackoverflow.com/questions/51353545

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

Vulnerabilities

No vulnerabilities reported

Install sbrt2017

You can download it from GitHub.
You can use sbrt2017 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

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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