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Natural Language Processing (NLP) in Speech Recognition for Kids | by SoapBox | Jun, 2021

An abstract image that depicts natural language processing. Shapes, like a circle, square, and hexagon are in the background, overlaid with a network of lines, and a silhouette of a young child’s face.

Welcome to “Lessons from our Voice Engine,” a series of blog posts by members of our Engineering and Speech Tech teams that explain, at a high level, how our voice engine works.

This first lesson comes from Nick Parslow, a Computational Linguist and member of our Speech Tech team at SoapBox Labs.

What is NLP?

In speech recognition systems like the SoapBox voice engine, NLP is used to build what are called language models — statistical models of language that can predict the next word based on the context. Language models are essential to help disambiguate similar sounding phrases. A great example of this is “white shoes” and “why choose.”

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Building a language model requires “normalization” of text — taking, for example, all instances of “ice-cream” and “icecream” and converting them to the same form. Without that normalization, the computer thinks of them as completely unrelated words.

Another use of NLP in speech recognition — in particular for English — is to work out the pronunciation of a word. This may be difficult for a machine to work out automatically (comparing “though” and “tough,” for example), so it may involve a mix of manual and automatic estimation.

What role does NLP play at SoapBox?

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