asr-evaluation | Python module for evaluating ASR hypotheses | Speech library

by belambert Python Version: v2.0.2 License: Apache-2.0

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

kandi X-RAY | asr-evaluation Summary

asr-evaluation is a Python library typically used in Artificial Intelligence, Speech, Pytorch, Neural Network applications. asr-evaluation has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Python module for evaluting ASR hypotheses (i.e. word error rate and word recognition rate). This module depends on the [editdistance] project, for computing edit distances between arbitrary sequences. The formatting of the output of this program is very loosely based around the same idea as the align.c program commonly used within the Sphinx ASR community. This may run a bit faster if neither instances nor confusions are printed. Please let me know if you have any comments, questions, or problems.

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asr-evaluation has a low active ecosystem.

It has 223 star(s) with 71 fork(s). There are 14 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 7 have been closed. On average issues are closed in 19 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of asr-evaluation is v2.0.2

Quality

asr-evaluation has 0 bugs and 0 code smells.

Security

asr-evaluation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

asr-evaluation code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

asr-evaluation is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

asr-evaluation releases are available to install and integrate.

Build file is available. You can build the component from source.

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

asr-evaluation saves you 153 person hours of effort in developing the same functionality from scratch.

It has 381 lines of code, 24 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Process a line pair
Print the difference between two sequences
Prints the examples of a given reference
Calculates the number of mutations that occur in the sequence
Removes head ID from a reference file
Remove the tail id from the reference lines
Returns the number of matches matching blocks
Calculate the total number of error codes
Print wers counts for each bin
Return the mean of a sequence
Return argument parser
Prints allusions
Set global variables

Get all kandi verified functions for this library.

asr-evaluation Key Features

No Key Features are available at this moment for asr-evaluation.

asr-evaluation Examples and Code Snippets

No Code Snippets are available at this moment for asr-evaluation.

Community Discussions

Trending Discussions on asr-evaluation

how to add filter to tweepy stream in an flask socketio application?

QUESTION

how to add filter to tweepy stream in an flask socketio application?

Asked 2018-May-05 at 19:11

With my flask-socketio app, I am trying to update all connected clients when I receive a new tweet. So following is my code.

...

ANSWER

Answered 2018-May-05 at 19:11

Since you are using gevent and doing networking through tweepy, it is required that you monkey patch the Python standard library so that it becomes compatible with gevent's async loop.

This is the code that you need to add to monkey patch:

Source https://stackoverflow.com/questions/50185742

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

Vulnerabilities

No vulnerabilities reported

Install asr-evaluation

You can download it from GitHub.
You can use asr-evaluation 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 contributions, it’s best to Github issues and pull requests. Proper testing and documentation suggested. Code of conduct is expected to be reasonable, especially as specified by the [Contributor Covenant](http://contributor-covenant.org/version/1/4/).

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