semvec/pypi-packages huggingface dataset:
transcribe-compare 0.2.4
Voicegain Compare transcription

# Utility to compare output transcript to reference

Uses [Ukkonen algorithm](https://www.sciencedirect.com/science/article/pii/S0019995885800462) to efficiently compute [Leveshtein distance](https://en.wikipedia.org/wiki/Levenshtein_distance) and character error rate (CER).

Additionally it can output alignment information.

## Usage

```
Usage: transcribe-compare [OPTIONS]

  Transcription compare tool provided by VoiceGain

Options:
  -r, --reference TEXT            source string
  -o, --output TEXT               target string
  -R, --reference_file FILENAME   source file path
  -O, --output_file FILENAME      target file path
  -a, --alignment                 Do you want to see the alignment result?
                                  True/False
  -e, --error_type [CER|WER]
  -j, --output_format [JSON|TABLE]
  -l, --to_lower                  Do you want to lower all the words?
                                  True/False
  -p, --remove_punctuation        Do you want to remove all the punctuation?
                                  True/False
  -P, --to_save_plot              Do you want to see the windows? True/False
  -s, --to_edit_step INTEGER      Please enter the step
  -w, --to_edit_width INTEGER     Please enter the width
  --help                          Show this message and exit.
  ```

## Dependencies

+ click
+ inflect
+ re
+ nltk
+ metaphone
+ matplotlib

# Sample Commands

```
python transcribe-compare -R sample_data/The_Princess_and_the_Pea-reference.txt -O sample_data/The_Princess_and_the_Pea-output-1.txt -e CER
```

# HTML Output

![HTML Output: Single Compare - Stats](/images/compare-single-stats.PNG)

# Related code

There is a script available that using `transcribe-compare` to compare results from Voicegaing and Google recognizers. You can find it here: https://github.com/voicegain/platform/tree/master/utility-scripts/test-transcribe

## Acknowledgements

Contributed by [VoiceGain](https://www.voicegain.ai).

VoiceGain provides Deep-Neural-Network-based Speech-to-Text (ASR) available in Cloud and also as an Edge Deployment.
Accessible via RESTful Web API or MRCP v2 interface.
Is suitable both for continuous large-vocabulary transcription (real-time or off-line) and for recognition using context-free grammars (e.g. GRXML).
In addition to this VoiceGain platform provides API-driven method to modify models used in speech-to-text. It is possible to modify language model, pronunciation model, and the acoustic DNN model.


## License

[MIT Â© VoiceGain](./LICENSE)
adaptiveagatepy 0.9.79
Python APIs for accessing sequencing data in the Adaptive Biotechnologies Agate Datastore

Adaptive Agate Python SDK
*************************
Early Release Phase - November, 2020

This platform is in an early release phase; if you are comfortable working with early-release software and would like access, please contact agate-support@adaptivebiotech.com.

Adaptive Agate is a new, modern platform designed by Adaptive Biotechnologies to share data with our immunoSEQ&reg; research customers and assist with downstream analysis. The platform consists of four components:

- A cloud-based SQL Server database containing metadata about samples such as the total number of templates found and sample-level metrics such as clonality. 
- Per-sample files containing detailed sequence-level information, stored in and accessed via Azure Blob Storage. 
- A set of REST functions providing common algorithms and analyses. 
- An easily-installed Python library that provides simple access to all of the above.

Access to these resources are secured using Microsoft Azure Active Directory credentials. Customers can associate their existing email addresses with Agate accounts and, in many cases, use existing enterprise or Microsoft credentials.

While we expect most users will use Python to access Agate data and functions, any tool or development environment that can access SQL, Azure Blob and HTTPS resources using Active Directory authentication is supported. For example, we supply a Microsoft Excel template (Windows only) that can automatically download data into worksheets and pivot tables for direct analysis in that environment.  For more information, visit the Agate documentation website at www.adaptiveagate.com.

How to get the Adaptive Agate Python SDK
========================================
Packages for the Adaptive Agate Python SDK (adaptiveagatepy) are available from PyPi and Anaconda using the mechanisms below.

To install from PyPi using PIP:
.. code-block:: 

	pip install adaptiveagatepy

To install from Anaconda using conda:
.. code-block:: 

	conda install -c adaptivebiotech adaptiveagatepy

immunoSEQ is for research use only and not for use in diagnostic procedures.

Copyright 2020 Adaptive Biotechnologies, All Rights Reserved.