Amazon Announces New Text-to-Speech and AI Services

[tubemonkey]

AWS Announces Three New Amazon AI Services

Amazon Lex, the technology that powers Amazon Alexa, enables any developer to build rich, conversational user experiences for web, mobile, and connected device apps; preview starts today

Amazon Polly transforms text into lifelike speech, enabling apps to talk with 47 lifelike voices in 24 languages

Amazon Rekognition makes it easy to add image analysis to applications, using powerful deep learning-based image and face recognition

SEATTLE--(BUSINESS WIRE)--Nov. 30, 2016-- Today at AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced three Artificial Intelligence (AI) services that make it easy for any developer to build apps that can understand natural language, turn text into lifelike speech, have conversations using voice or text, analyze images, and recognize faces, objects, and scenes. Amazon Lex, Amazon Polly, and Amazon Rekognition are based on the same proven, highly scalable Amazon technology built by the thousands of deep learning and machine learning experts across the company. Amazon AI services all provide high-quality, high-accuracy AI capabilities that are scalable and cost-effective. Amazon AI services are fully managed services so there are no deep learning algorithms to build, no machine learning models to train, and no up-front commitments or infrastructure investments required. This frees developers to focus on defining and building an entirely new generation of apps that can see, hear, speak, understand, and interact with the world around them. To learn more about Amazon Lex, Amazon Polly, or Amazon Rekognition, visit: https://aws.amazon.com/amazon-ai

Until now, very few developers have been able to build, deploy, and broadly scale apps with AI capabilities because doing so required access to vast amounts of data, and specialized expertise in machine learning and neural networks. Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g. automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models. And this process must be repeated for every object, face, voice, and language feature in an application. Amazon AI services eliminate all of this heavy lifting, making AI broadly accessible to all app developers by offering Amazon’s powerful and proven deep learning algorithms and technologies as fully managed services that any developer can access through an API call or a few clicks in the AWS Management Console. Amazon AI services make the full power of Amazon’s natural language understanding, speech recognition, text-to-speech, and image analysis technologies available at any scale, for any app, on any device, anywhere.

The voice recognition technology has certainly come a LONG way since I first tried using Dragon's Naturally Speaking software back in the early(?) 1990s. I remember having to put on a headset and sit for hours dictating into Dragon's app to get it to learn my voice, and it never really performed that well. But that was over two decades ago! Also, a tablet or smartphone is exponentially faster with more memory than the early 1990s PCs. That was an era of 80286 processors and 640 KB or RAM.

At any rate, voice recognition and AI technologies have both advanced quite a bit now, and the computers as well. We are still not to the HAL 9000 level, but that is probably a good thing...

[frahse]

It sounds great.

[Dopedangel]

Originally Posted by jswinden

The voice recognition technology has certainly come a LONG way since I first tried using Dragon's Naturally Speaking software back in the early(?) 1990s. I remember having to put on a headset and sit for hours dictating into Dragon's app to get it to learn my voice, and it never really performed that well. But that was over two decades ago! Also, a tablet or smartphone is exponentially faster with more memory than the early 1990s PCs. That was an era of 80286 processors and 640 KB or RAM.

At any rate, voice recognition and AI technologies have both advanced quite a bit now, and the computers as well. We are still not to the HAL 9000 level, but that is probably a good thing...

Google is using its deep mind technology to learn to lip read. Already is more accurate than lip reading experts. The speed of the improvements that they are getting with machine learning in 5yrs-10yrs I expect them to be able to transcribe translate and maybe even voice a hundred languages. As more time passed I was thinking the world will be dominated by a few languages like English and Mandarin but now I feel in a decade the chances are we will get an internet where you can read write any language and all will understand as your browser will translate the whole thing into the language of your choice. It already does but you can tell it's a translation.

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