speech-recognition-evaluation

Evaluate results from ASR/Speech-to-Text quickly

Showing:

Popularity

Downloads/wk

3

GitHub Stars

19

Maintenance

Last Commit

1yr ago

Contributors

1

Package

Dependencies

4

Size (min+gzip)

29.0KB

License

Apache-2.0

Type Definitions

Tree-Shakeable

No?

Categories

Readme

Automatic Speech Recognition (ASR) Evaluation

If you're using any Speech-to-Text or Speech Recognition engine to generate transcriptions from your audio/video content, then you can use this tool to compare how well it is doing against a human generated transcription. If you're not sure how to generate transcription, you can take a look here for list of tutorials to help you get started.

What can this utility do?

This is a simple utility to perform a quick evaluation on the results generated by any Speech to text (STT) or Automatic Speech Recognition (ASR) System.

This utility can calculate following metrics -

  • Word Error Rate (WER), which is a most common metric of measuring the performance of a Speech Recognition or Machine translation system
  • Levenshtein Distance calculated at word level.
  • Number of Word level insertions, deletions and mismatches between the original file and the generated file.
  • Number of Phrase level insertions, deletions and mismatches between the original file and the generated file.
  • Color Highlighted text Comparison to visualize the differences.
  • General Statistics about the original and generated files (bytes, characters, words, new lines etc.)

The utility also performs the pre-processing or normalization of the text in the provided files based on following operations -

  • Remove Speaker Name: Remove Speaker name at the beginning of the line.
  • Remove Annotations: Remove any custom annotations added during transcriptions.
  • Remove Whitespaces: Remove any extra white spaces.
  • Remove Quotes: Remove any double quotes
  • Remove Dashes: Remove any dashes
  • Remove Punctuations: Remove any punctuations (.,?!)
  • Convert contents to lower case

Pre-requisites

Make sure that you have NodeJS v8+ installed on your system.

Installation

npm install -g speech-recognition-evaluation

Verify installation by simply running:

asr-eval

Usage

Simplest way to run your first evaluation is by simply passing original and generated options to asr-eval command. Where, original is a plain text file containing original transcript to be used as reference; usually this is generated by human beings. And generated is a plain text file containing generated transcript by the STT/ASR system.

asr-eval --original ./original-file.txt --generated ./generated-file.txt

This would print simply the Word Error Rate (WER) between the provided files. This is how the output should look like:

Word Error Rate (WER): 13.61350109561817%

To find more information about all the available options:

asr-eval --help

All the available usage options would be printed:

Synopsis

  $ asr-eval --original file --generated file           
  $ asr-eval [options] --original file --generated file 
  $ asr-eval --help                                     

Options

  -o, --original file         Original File to be used as reference. Usually, this should be the            
                              transcribed file by a Human being.                                            
  -g, --generated file        File with the output generated by Speech Recognition System.                  
  -e, --wer                   Default: true. Print Word Error Rate (WER).                                   
  --distance                  Default: false. Print total word distance after comparison.                   
  -e, --stats                 Default: false. Print statistics about original and generate files, before    
                              and after pre-processing. Also prints statistics about word level and phrase  
                              level differences.                                                            
  --pairs                     Default: false. Print all the difference pairs with type of difference.       
  -c, --textcomparison        Default: false. Print the text comparison between two files with              
                              highlighting.                                                                 
  -s, --removespeakers        Default: true. Remove the speaker at the start of each line in files before   
                              calculations. The speaker should be separated by colon ":" i.e. speaker_name: 
                              text For e.g. "John Doe: Hello, I am John." would get converted to simply     
                              "Hello, I am John."                                                           
  -a, --removeannotations     Default: true. Remove any custom annotations in the transcript before         
                              calculations. This is useful when removing custom annotations done by human   
                              transcribers.  Anything in square brackets [] are detected as annotations.    
                              For e.g. "Hello, I am [inaudible 00:12] because of few reasons." would get    
                              converted to "Hello, I am because of few reasons."                            
  -w, --removewhitespaces     Default: true. Remove any extra white spaces before calculations.             
  -q, --removequotes          Default: true. Remove any double quotes '"' from the files before             
                              calculations.                                                                 
  -d, --removedashes          Default: true. Remove any dashes (hyphens) "-" from the files before          
                              calculations.                                                                 
  -p, --removepunctuations    Default: true. Remove any punctuations ".,?!" from the files before           
                              calculations.                                                                 
  -l, --lowercase             Default: true. Convert both files to lower case before calculations. This is  
                              useful if evaluation needs to be done in case-insensitive way.                
  -h, --help                  Print this usage guide.                              

Getting help

If you need help installing or using the utility, please give a shout out in our slack channel

If you've instead found a bug or would like new features added, go ahead and open issues or pull requests against this repo!

Rate & Review

Great Documentation0
Easy to Use0
Performant0
Highly Customizable0
Bleeding Edge0
Responsive Maintainers0
Poor Documentation0
Hard to Use0
Slow0
Buggy0
Abandoned0
Unwelcoming Community0
100
No reviews found
Be the first to rate

Alternatives

No alternatives found

Tutorials

No tutorials found
Add a tutorial