Saturday, July 13, 2019

DeepMorse - Web based tool for CW Puzzles and Training





Introduction 


I started working on a new DeepMorse project recently.  The idea behind this project is to create a web site that contains curated Morse code audio clips.   The website would allow subscribers to upload annotated CW audio clips (MP3, WAV, etc) and associated metadata.

As a subscriber you would be able to provide the story behind the clip as well as some commentary or even photos. After uploading the site would show the graphical view  of the audio clip much like the modern Software Defined Radios (SDRs) and users would be able to play back the audio and see the metadata.

Since this site would contain "real world" recordings and some really difficult to copy audio clips, this   would also provide ultimate test of your CW copying  skills. The system would save a score on your copying accuracy before it gives you the "ground truth" of annotated audio.  You could compete for the top scores with all the other CW aficionados.

The site could also be used to share historical records of curated Morse code audio materials with the ham radio  community. For CW newbies the site would have a treasure trove of different kinds of training materials when you get tired of listening ARRL morse practice MP3 files.  For experienced CW operators you could share some of your best moments when working using your favorite operating mode, teaching newbies how to catch the big fish.

User Interface

I wanted to experiment combining audio and graphical waveform view of the audio together, giving the user ability to listen, scroll back and re-listen as well as zoom into the waveform.

Part of the user interface is also the free text form where user can enter the text they heard in the audio clip.  By pressing "Check" button the system will calculate the accuracy compared to the "ground truth" text.  System is using normalized Levenshtein method to calculate the accuracy in percentage (0...100%) where 100% is perfect copy.

Figure 1. below shows the main listening view.
Figure 1. DeepMorse User Interface


Architecture

I wrote this web application using Python Django web framework and it took only a few nights to get the basic structure together.  The website is running in AWS using serverless Lambda functions and serverless Aurora RDS MySQL database.  The audio files are stored into an S3 bucket.

Using serverless database backend sounds like oxymoron, since there is a database server managed by AWS.  It also brings some challenges such as slow "cold start" that will be visible for end users. When you click the "Puzzles" menu you normally will get this view (see Figure 2. below).

Figure 2. Puzzles View 















However, if the serverless database server has timed out due to no activity, it will take more than 30 seconds to come up.  By this time the front end webserver has also timed out and the user will see this below instead (see Figure 3.).  A simple refresh of the browser will fix the situation and both the front end and the backend will be then available. 

Figure 3.  Serverless "Time Out" error message
















So what is then the benefit of using AWS serverless technology?   The benefit is that you get billed only for usage and if the application is not used 24x7 this means significant cost savings. For a hobby project like DeepMorse I am able to run the service very cost efficiently. 

The other benefit of serverless technologies is automatic scaling - if the service becomes suddenly hugely popular the system is able to scale up rapidly. 

Next Steps

I am looking for some feedback from early users trying to figure out what features might be interesting for Morse code  aficionados. 

73 de Mauri 
AG1LE


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