Genderless Voice

Genderless Voice: A More Inclusive Future with Tech

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New technologies are being developed to address the social issue of AI voice and to make the technology as inclusive as possible.

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Why Voice Isnt Enough To Be Smart

Why Voice Isn’t Enough to be Smart

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Audio Analytic has already developed AI technology that can give devices a sense of hearing, accurately recognising sounds, beyond speech and music.

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Fixing A Few Common Errors When Publishing Your Google Assistant App

Fixing a few common errors when publishing your Google Assistant App

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A look at some common DialogFlow and Google Actions errors, and their solutions: Invalid Privacy Policy, Invalid Invocation Name, and App…

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An Idiot’s Guide To Word2vec Natural Language Processing

An Idiot’s Guide to Word2vec Natural Language Processing

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Word2vec is arguably the most famous face of the neural network natural language processing revolution.

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Fixing The Voice First Party Third Party Gap With Schema.org

Fixing the Voice First-Party / Third-Party Gap with schema.org

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Leveraging website data with schema.org markup could become essential for voice app developers.

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Bus

“Alexa, when is the next bus?”

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Amazon was invited to support the 3rd annual Makeathon, a 36-hour prototyping and design competition.

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Improve Your Machine Learning Models With Compressed Audio

Improve your machine learning with compressed audio

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In machine learning, you need to know what’s in your audio data. Discover how data augmentation with codec compressed audio can help your models generalize.

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Why Voice Assistants Are Beneficial To Children

Why Voice Assistants are Beneficial to Children

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The impact of voice assistants on today’s youth is actually more helpful than you may think. Luckily, there are a plethora of fun, sound-based games.

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Artificial Emotional Intelligence

The state of artificial emotional intelligence today

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Artificial Emotional Intelligence is a relatively new field, but one in which there is tremendous activity. Supported by a plethora of new open-source tools and machine learning frameworks, a programmer can now build a first prototype of an emotion-aware dialog machine in about two working days. But how good is the technology? And how can we develop better emotion AI?

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