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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