tensorflow-wavenet | speech recognition | Speech library

by Deeperjia Python Version: Current License: No License

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

kandi X-RAY | tensorflow-wavenet Summary

tensorflow-wavenet is a Python library typically used in Artificial Intelligence, Speech, Tensorflow applications. tensorflow-wavenet has no bugs, it has no vulnerabilities and it has low support. However tensorflow-wavenet build file is not available. You can download it from GitHub.

speech recognition based on tensorflow 1.0.0

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tensorflow-wavenet has a low active ecosystem.

It has 134 star(s) with 71 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 0 have been closed. On average issues are closed in 1050 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-wavenet is current.

Quality

tensorflow-wavenet has 0 bugs and 0 code smells.

Security

tensorflow-wavenet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

tensorflow-wavenet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

tensorflow-wavenet does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

tensorflow-wavenet releases are not available. You will need to build from source code and install.

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

tensorflow-wavenet saves you 114 person hours of effort in developing the same functionality from scratch.

It has 288 lines of code, 15 functions and 4 files.

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

Top functions reviewed by kandi - BETA

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

Train the model
Creates a batch of data batches
Returns the next batch
Resets the batch pointer
Resolve the residual block
Performs batch norm
The aconv1d layer
1d layer
Performs an activation layer

Get all kandi verified functions for this library.

tensorflow-wavenet Key Features

No Key Features are available at this moment for tensorflow-wavenet.

tensorflow-wavenet Examples and Code Snippets

No Code Snippets are available at this moment for tensorflow-wavenet.

Community Discussions

Trending Discussions on tensorflow-wavenet

reading files in google cloud machine learning

QUESTION

reading files in google cloud machine learning

Asked 2017-Mar-13 at 14:06

I tried to run tensorflow-wavenet on the google cloud ml-engine with gcloud ml-engine jobs submit training but the cloud job crashed when it was trying to read the json configuration file:

...

ANSWER

Answered 2017-Mar-13 at 14:06

Python's open function cannot read files from GCS. You will need to use a library capable of doing so. TensorFlow includes one such library:

Source https://stackoverflow.com/questions/42761075

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

Vulnerabilities

No vulnerabilities reported

Install tensorflow-wavenet

You can download it from GitHub.
You can use tensorflow-wavenet 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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