Updated: Jan 24, 2022
Solution Kit Course Shorts help students get introductions to courses or refresh topics or even transmit summaries over low bandwidth connections. In this challenge, we are inviting to build a solution for creating summaries from video/audio course content. You can choose any course of your choice. Please see below a sample solution kit to jumpstart your solution on creating a course shorts. To install this kit, scroll down to refer sections Kit Deployment Instructions and Instruction to Run. Complexity : Simple This kit transcribes audio and creates a summary out of transcription.
Development Environment
VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers. Jupyter Notebook is used for our development.
jupyterby jupyter
14404 Version:CurrentJupyter metapackage for installation, docs and chat
jupyterby jupyter
Python 14404 Version:Current License: Permissive (BSD-3-Clause)
Exploratory Data Analysis
For extensive analysis and exploration of data, and to deal with arrays, these libraries are used. They are also used for performing scientific computation and data manipulation.
pandasby pandas-dev
38689 Version:v2.0.2Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandasby pandas-dev
Python 38689 Version:v2.0.2 License: Permissive (BSD-3-Clause)
numpyby numpy
23755 Version:v1.25.0rc1The fundamental package for scientific computing with Python.
numpyby numpy
Python 23755 Version:v1.25.0rc1 License: Permissive (BSD-3-Clause)
Text mining
Libraries in this group are used for analysis and processing of unstructured natural language. The data, as in its original form aren't used as it has to go through processing pipeline to become suitable for applying machine learning techniques and algorithms.
spaCyby explosion
26383 Version:v3.2.6💫 Industrial-strength Natural Language Processing (NLP) in Python
spaCyby explosion
Python 26383 Version:v3.2.6 License: Permissive (MIT)
Transcribing
Transcribing libraries help in converting speech to text.
DeepSpeechby mozilla
22108 Version:v0.10.0-alpha.3DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
DeepSpeechby mozilla
C++ 22108 Version:v0.10.0-alpha.3 License: Weak Copyleft (MPL-2.0)
Machine Learning
Machine learning libraries and frameworks here are helpful in generating state-of-the-art summarization.
scikit-learnby scikit-learn
54584 Version:1.2.2scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python 54584 Version:1.2.2 License: Permissive (BSD-3-Clause)
transformersby huggingface
104111 Version:v4.30.2🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
transformersby huggingface
Python 104111 Version:v4.30.2 License: Permissive (Apache-2.0)
Kit Solution Source
speech-summarizerby kandikits
0 Version:v1.0.0Transcribes and summarizes speech or audio
speech-summarizerby kandikits
Jupyter Notebook 0 Version:v1.0.0 License: Permissive (Apache-2.0)
Deployment Information
For Windows OS, Download, extract and double-click kit_installer file to install the kit. Note: Do ensure to extract the zip file before running it. The installation may take from 2 to 10 minutes based on bandwidth. 1. When you're prompted during the installation of the kit, press Y to launch the app automatically and execute cells in the notebook by selecting Cell --> Run All from Menu bar to see how the speech summariser works. It is loaded with sample audio file. 2. To run the app manually, press N when you're prompted and locate the zip file speech-summarizer.zip 3. Extract the zip file and navigate to the directory speech-summarizer-main 4. Open command prompt in the extracted directory speech-summarizer-main and run the command jupyter notebook For other Operating System, 1. Click here to install python 2. Click here to download the repo 3. Extract the zip file and navigate to the directory speech-summarizer-main 4. Open terminal in the extracted directory speech-summarizer-main 5. Install dependencies by executing the command pip install -r requirements.txt 6. Run the command jupyter notebook
Instruction to Run
Follow below instructions to run the solution. 1. Locate and open the Course Shorts App.ipynb notebook from the Jupyter Notebook browser window. 2. Execute cells in the notebook by selecting Cell --> Run All from Menu bar For using with your audio file, 1. In Jupyter Notebook, set the variable INPUT_AUDIO_FILE to an audio file of your choice meeting below criteria. a) wav file format b) sample rate of 16KHz c) mono type audio channel 2. Execute cells in the notebook by selecting Cell --> Run All from Menu bar 3. The output file will be generated in the directory speech-summarizer-main/output/ from the kit_installer.bat location Sample Input: speech-summarizer-main/input/speech.wav - an audio file matching aforementioned criteria Output: speech-summarizer-main/output/summarised_text.txt - a text file containing summary of the input audio You can additionally build interfaces to the speech summariser and other enhancements for additional score. For any support, you can direct message us at #help-with-kandi-kits
Troubleshooting
1. While running batch file, if you encounter Windows protection alert, select More info --> Run anyway 2. During kit installer, if you encounter Windows security alert, click Allow
Support
For any support, you can direct message us at #help-with-kandi-kits