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Showing posts tagged with Alexa science

December 11, 2018

Chengwei Su

A new technique that lets different natural-language-understanding modules independently calibrate their judgments about whether they should handle a given utterance helps improvements reach Alexa customers more efficiently.

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December 07, 2018

Ruhi Sarikaya

In an invited talk at the second NeurIPS workshop on Conversational AI today, Alexa scientist Ruhi Sarikaya will focus on the role of context in redefining human-computer interaction through natural language.

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December 04, 2018

Behnam Hedayatnia

The addition of information about the last few turns of conversation and a small set of standard "dialogue act" tags boost Alexa's ability to determine the topic of an utterance by 35%.

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November 19, 2018

Trevor Wood

Alexa researchers show that their new neural-network-based text-to-speech system can learn how to read news in the style of a TV newscaster from just a few hours of training data.

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October 31, 2018

Young-Bum Kim

Amazon researcher Young-Bum Kim describes some new modifications to the machine learning model that selects the one skill out of thousands best suited to a particular customer request.

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October 25, 2018

Larry Hardesty

At this year's Conference on Empirical Methods in Natural Language Processing (EMNLP), Amazon researchers are cohosting what they hope will be the first in a series of annual workshops that will both catalyze and publicize research on automatic fact verification.

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October 04, 2018

Jun Yang

Using an Echo's microphone array to perform sound-source localization could provide Alexa with useful information about a customer's physical context and enable the use of claps, taps, or snaps as control signals.

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October 02, 2018

Chieh-Chi Kao

Alexa scientists describe two different approaches to the problem of audio event detection, the research topic that led to the new Alexa Guard home security feature. 

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September 28, 2018

Vishal Naik

Last week, Amazon announced a redesigned Echo Show and the Alexa Presentation Language, which lets third-party developers build “multimodal” skills that coordinate voice and graphics. VIshal Naik explains the science behind a multimodal system that uses on-screen data to disambiguate voice requests.

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September 26, 2018

Zeynab Raeesy

The science behind Alexa's newly announced whisper mode, which enables her to respond to customers' whispers by whispering back.

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September 04, 2018

Young-Bum Kim

Classifying "domains", or topics of conversation, is so central to natural-language understanding that some systems have modules that just look for out-of-domain utterances. Amazon researchers show that training out-of-domain classifiers together with domain recognizers improves their performance.

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August 31, 2018

Viktor Rozgic

At Interspeech 2018, Amazon scientists report a new system that learns to distinguish sounds produced by media players, such as TVs and radios, from sounds of ordinary household activity, to reduce false positives from Alexa's speech recognizers still further.

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August 29, 2018

Larry Hardesty

Amazon papers at Interspeech 2018 examine ways that interaction histories can improve customers' Alexa experiences, from "collaborative filtering" to infer customers' tastes to methods that use the immediate "context" of a customer's requests to increase the accuracy of speech understanding systems.

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August 27, 2018

Arpit Gupta

Alexa AI machine-learning scientist Chetan Naik and speech scientist Arpit Gupta describe their Interspeech paper on "contextual slot carryover," a crucial element of Alexa's ability to conduct natural, multiround conversations.

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August 24, 2018

Larry Hardesty

3 questions with Björn Hoffmeister, the senior manager for machine learning in the Alexa Automatic Speech Recognition group, about this year's Interspeech conference and research trends in the speech technology field.

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