There Can be No True Scottish Speech Recognition System

Maggie Reid1, and Dr. Gregor MacGregor2

1 Department of Interracial Computer Science, Cranberry-Lemon University, Pittsburgh, PA, USA

2 Department of Linguistics, William Wallace University, Edinburgh, Scotland

Abstract

With the advances of machine learning and neural networks advancing the fields of natural language processing, many applications are being developed every day across the world to interface man and machine through Speech Recognition Systems (SRS). Studies have shown that modern day voice recognition technology not only struggles to understand the Scottish accent, but it consistently fails to create one understandable to the local public of Scotland. A novel neural network has been developed to create an interface between machine and Scott. Additional nodes and  percussive layers were added to the neural network allowing for the language processor to extract information from mumbling utterances normally non differentiable to most human ears but extremely meaningful to Scotsmen. While some Scotsmen were able to interface with the network when using regionally specific training data, it was determined that regions differed from pub to pub. A further analysis of the accent revealed that the Scottish dialect outside of one town is non convergent and it is mathematically impossible for man or machine to create a true Scotsman. 

Keywords: Speech Recognition Systems, Natural Language Processing, Scottish Accent, Voice Recognition

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Published by B McGraw

B McGraw has lived a long and successful professional life as a software developer and researcher. After completing his BS in spaghetti coding at the department of the dark arts at Cranberry Lemon in 2005 he wasted no time in getting a masters in debugging by print statement in 2008 and obtaining his PhD with research in screwing up repos on Github in 2014. That's when he could finally get paid. In 2018 B McGraw finally made the big step of defaulting on his student loans and began advancing his career by adding his name on other people's research papers after finding one grammatical mistake in the Peer Review process.

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