Smart home devices don't exist because humans are increasingly getting lazy. They exist because they make our lives infinitely easier. After all, who would want to get up to switch the lights on and off when you can just command them to? For this summer sale promo, you can enjoy massive discounts on smart devices and smart plugs that turn regular appliances into smart ones. Plus, if you spend $50, you'll also receive $10 in store credit that you can spend on anything.
"Start navigation, please," said the driver in the car with noisy passengers. Within seconds, a speech recognition system identified the command and activated the navigation system simply by reading the driver's lips. In another instance, a patient in a hospital with breathing tubes placed below their vocal cords, finds it difficult to speak. The helper uses SRAVI – a mobile app that uses Liopa's lip-reading technology – to scan the patient's face while they silently mouth a sentence. The Artificial Intelligence (AI)-assisted system then displays three probable statements of what the patient may be trying to say.
The Linux Foundation is teaming up with companies like Target, Microsoft and Veritone to create the Open Voice Network, an initiative designed to "prioritize trust and standards" in voice-focused technology. Jon Stine, executive director of the Open Voice Network, told ZDNet that the rapid growth of both the availability and adoption of voice assistance worldwide -- and the future potential of voice as an interface and data source in an artificial intelligence-driven world -- makes it important for certain standards to be communally developed. Devices and applications are increasingly incorporating voice activation and navigation functions, and Mike Dolan, senior vice president at the Linux Foundation, said the network was a "proactive response to combating deep fakes in AI-based voice technology." "Voice is expected to be a primary interface to the digital world, connecting users to billions of sites, smart environments and AI bots. It is already increasingly being used beyond smart speakers to include applications in automobiles, smartphones and home electronics devices of all types. Key to enabling enterprise adoption of these capabilities and consumer comfort and familiarity is the implementation of open standards," Dolan said, adding that the organization was "excited to bring it under the open governance model of the Linux Foundation to grow the community and pave a way forward."
If you haven't added voice control to your smart home collection, now is a great time for some tech upgrades. As of June 3, Amazon has tons of Echo, Echo Dot, and Echo Show devices on sale to help you automate your entertainment, connect with loved ones, and control your other smart devices using your voice. Just think: the right smart speaker will let you call your mom, turn on some tunes, and adjust your smart lighting without ever leaving the couch or picking up your phone. With so many options, picking a smart speaker or smart home hub can seem daunting. If you're not quite sure which Echo device is right for your lifestyle, check out our Echo vs Echo dot comparison for a full breakdown, and read below to discover the current deals.
Devices and tools activated through speaking will soon be the primary way people interact with technology, yet none of the main voice assistants, including Amazon's Alexa, Apple's Siri and Google Assistant, support a single native African language. Mozilla has sought to address this problem through the Common Voice project, which is now working to expand voice technology to the 100 million people who speak Kiswahili across Kenya, Uganda, Tanzania, Rwanda, Burundi and South Sudan. The open source project makes it easy for anyone to donate their voice to a publicly available database that can then be used to train voice-enabled devices, and over the past two years, more than 840 Rwandans have donated over 1,700 hours of voice data in Kinyarwanda, a language with over 12 million speakers. That voice data is now being used to help train voice chatbots with speech-to-text and text-to-speech functionality that has important information about COVID-19, according to Chenai Chair, special advisor for Africa Innovation at the Mozilla Foundation. A handful of major tech companies control the voice data that is currently used to train machine learning algorithms, posing a challenge for companies seeking to develop high-quality speech recognition technologies while also exacerbating the voice recognition divide between English speakers and the rest of the world.
Zhang, Daniel, Mishra, Saurabh, Brynjolfsson, Erik, Etchemendy, John, Ganguli, Deep, Grosz, Barbara, Lyons, Terah, Manyika, James, Niebles, Juan Carlos, Sellitto, Michael, Shoham, Yoav, Clark, Jack, Perrault, Raymond
Welcome to the fourth edition of the AI Index Report. This year we significantly expanded the amount of data available in the report, worked with a broader set of external organizations to calibrate our data, and deepened our connections with the Stanford Institute for Human-Centered Artificial Intelligence (HAI). The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Its mission is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public to develop intuitions about the complex field of AI. The report aims to be the most credible and authoritative source for data and insights about AI in the world.
TP-Link has today announced an updated version of its Deco mesh networking gear that now has voice control, through Amazon Alexa. The Deco Voice X20 packs in a smart speaker in every satellite point that enables users to control the smart parts of their home without buying more Echo Dots. The two pack you can buy at retail is said to cover 4,000 square feet in WiFi 6, with truly "seamless roaming." The hardware is pretty interesting to look at, too, with a white cylinder floating on a hot-rod red base. Mesh networks rely upon gadgets being strewn around your home in prominent places, not hidden behind cupboards. In order to encourage this, device makers have both made their gear look better, but also do more to ensure that they find a place in your heart.
This represents our fifth annual Voice AI predictions article and there is no question it is the most interesting and insightful to date. It is also the largest with over 100 predictions from 50 voice industry leaders. You will not that some of our guest contributors are confident enough to make multiple predictions. It increases the odds at least one of them will be correct. What is striking for our 2021 issue is the breadth of predictions and the interesting insights. The industry is simply more mature, has seen more, and has a better grasp on what is coming. I enjoyed reading this year's predictions and am sure you will as well. Despite the breadth of topics covered, there are at least two topics that arose with meaningfully higher frequency than the others. Predictions related to the rise of custom assistants were mentioned by at least 11 contributors followed by an increase focus on voice solution while on-the-go. Personalization, both in terms of the user preference and emotion recognition or empathy, and a rise in multimodal user experiences were next in line mentioned by about 10% of the contributors. After that, a number of topics showed some popularity ranging from more rapid voice AI adoption in customer service (including virtual humans) to more growth in voice assistant features for audio media. It was interesting to see two guests (Audrey Arbeeny and Kirill Petrov) mention an expected rise of voice assistant and custom synthetic voices in games, a couple who are optimistic about Apple making a big Siri update this year (Brian Roemmele and Max Child), and how AR might spur voice adoption (Joan Palmiter Bajorek and Craig Sanders).
In this paper, we propose and experiment with techniques for extreme compression of neural natural language understanding (NLU) models, making them suitable for execution on resource-constrained devices. We propose a task-aware, end-to-end compression approach that performs word-embedding compression jointly with NLU task learning. We show our results on a large-scale, commercial NLU system trained on a varied set of intents with huge vocabulary sizes. Our approach outperforms a range of baselines and achieves a compression rate of 97.4% with less than 3.7% degradation in predictive performance. Our analysis indicates that the signal from the downstream task is important for effective compression with minimal degradation in performance.
Artificial Intelligence (AI) technology evolves rapidly, and it has great potential in the future. According to the latest reports, the market size of AI is projected to reach $266.92 billion by 2027 with a Compound Annual Growth Rate (CAGR) of 33.2%. A lot of world-known brands and tech companies are already using AI-powered solutions to improve the service, engage customers, enhance customer experience, and increase efficiency and productivity. Text generation, face and speech recognition, automated translation, drug discovery are a few AI achievements that are worthy of your attention. AI-powered solutions are used by dozens of companies and implemented in different fields, changing a lot of industries and reshaping the landscape of health, learning, daily living, and so on.