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Monday, January 27, 2020

Alexa Self Learning to Correct Mistakes

In all conversation there is adjustments of our interactions.Good piece here that shows how this is being proposed for a common assistant.

Amazon Uses Self-Learning to Teach Alexa to Correct its Own Mistakes

The digital assistant incorporates a reformulation engine that can learn to correct responses in real time based on customer interactions .    By Jesus Rodriguez in Towards Data Science

 Digital assistant such as Alexa, Siri, Cortana or the Google Assistant are some of the best examples of mainstream adoption of artificial intelligence(AI) technologies. These assistants are getting more prevalent and tackling new domain-specific tasks which makes the maintenance of their underlying AI particularly challenging. The traditional approach to build digital assistant has been based on natural language understanding(NLU) and automatic speech recognition(ASR) methods which relied on annotated datasets. Recently, the Amazon Alexa team published a paper proposing a self-learning method to allow Alexa correct mistakes while interacting with users.

The rapid evolution of language and speech AI methods have made the promise of digital assistants a reality. These AI methods have become a common component of any deep learning framework allowing any developer to build fairly sophisticated conversational agents. However, the challenges are very different when operating at the scale of a digital assistant like Alexa. Typically, the accuracy of the machine learning models in these conversational agents is improved by manually transcribing ... '

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