semvec/pypi-packages huggingface dataset:
speech-intelligibility-index 1.0.2
Speech Intelligibility Index
Requires Python: >=3.6

A Python implementation of American National Standard ANSI S3.5-1997
**"Methods for Calculation of the Speech Intelligibility Index"**
This code is translated from Hannes Muesch's Matlab implementation.

This package includes both Python/Numpy and Python/JAX implementations.

There is a Google Colab that demonstrates how to use this code and shows
typical results.  This colab is a good place to start:
https://colab.research.google.com/drive/1bAnDpUUx5-BYkL3l3ukNVVnsLzEhy-ds.

For more information about the speech intelligibility index (SII) please see
the Acoustical Society of America (ASA) working group's web site at
https://sii.to/index.html.

To use these scripts successfully, you might want to be familiar with the
concepts and definitions of the Speech Intelligibility Index (SII).
You can obtain a copy of the standard at the ANSI webstore
https://webstore.ansi.org/standards/asa/ansiasas31997r2017

You can reach out to the members of the Acoustical Society of America (ASA)
Working Group S3-79, which is in charge of reviewing that standard, at
https://sii.to/index.html.
videoslides 1.0.0
Package made to obtain a text transcription from a video, with a flow from video to frames to structured frames to transcription in a json file

# Video Slides

Package made to obtain a text transcription from a video, with a flow from video to frames to structured frames to transcription in a json file 
Paquete hecho para obtener una transcripcion desde un video, con un flujo que inicia con un video se obtienen sus frames y finalmente se extrae la transcripcion estructurada 

## Instalacion:

Mediante el siguiente comando :

pip install videoslides

## Ejemplos de uso

    # Crear clase de Video

    video1 = Video(string, 100, 1, True)
    video1.clean_frames()
    video1.set_data()
    video1.set_slides() 
    video1.set_transcription()


    print(video1.data)
    print(video1.slides)
    print(video1.transcription)
    # ploteo(video1.video_name , video1.data) # grafica