CTO and co-founder, OTO.ai, Nico Perony, shares how emotion and sentiment detection can be used to improve CX. read more
Yesterday I posted about how speech recognition systems, voice assistants, have trouble with different accents like Irish accents, Welsh accents, Scottish accents, Northern accents and how hard it is to actually train those systems based on accents because a different accent is essentially like a different language. read more
Dive deep into one of the core technologies that underpins the voice assistants you know and love, with one of the world’s leading speech recognition experts, Catherine Breslin.
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What is speech recognition and how does it work?
Automatics speech recognition (also known as ASR) is a suite of technology that takes audio signals containing speech, analysis it and converts it into text so that it can be read and understood by humans and machines. It’s the technology that makes voice assistants like Amazon Alexa able to understand what a user says.
There’s obviously a whole lot more to it that than, though. So, in today’s episode, we’re speaking to one of the most knowledgable and experienced speech recognition minds the world has to offer, Catherine Breslin, about just exactly what’s going on under the hood of automatic speech recognition technology and how it actually works.
Catherine Breslin studied speech recognition at Cambridge, before working on speech recognition systems at Toshiba and eventually on the Amazon Alexa speech recognition team where she met the Godfather of Alexa, Jeff Adams. Catherine then joined Jeff at Cobalt Speech where she currently creates bespoke speech recognition systems and voice assistants for organisations.
In this episode, you’ll learn how one of the fundamental voice technologies works, from beginning to end. This will give you a rounded understanding of automatic speech recognition technology so that, when you’re working on voice applications and conversational interfaces, you’ll at least know how it’s working and then be able to vet speech recognition systems appropriately.