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How Companies Will Eliminate Privacy Concerns With On-Premise Conversational AI

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With every new technological advancement, there's always someone poking at it from behind the computer screen, trying to find a vulnerability. This isn't new (Antheus biometric data breach, Robinhood data security incident, anyone?), but it is something that the average consumer doesn't think about enough. One of the biggest blind spots most of us have is surrounding the privacy of our data with voice assistants like Siri or Alexa. Technologies like speech-to-text software and conversational artificial intelligence (AI) are steadily increasing in popularity, and this means we need to start considering the privacy implications more seriously. Text-to-speech tools and chatbots are quickly becoming everyday technologies for businesses.


Artificial intelligence -- A Modern ERA

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Artificial intelligence (AI) is a category of software that can do things that would normally need human intelligence, like vision, speech recognition, decision-making, and language translation. Artificial intelligence does not have to be sentient; in fact, the term "artificial intelligence" was coined to differentiate it from natural intelligence. It can also apply to any technology that enables computers or machines to perform jobs that would otherwise necessitate human intelligence. An AI can study the data strings it needs to complete its work. The machine will analyze the data and use it to improve its overall performance. As a result, the machine can respond fast to a crisis.


24 Useful Open Datasets for Natural Language Processing

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Natural language processing forms the foundation of innovation in artificial intelligence. We want machines that sound like us, understand us, and take on tasks previously only possible through human interaction. Until then, developers can build and train with these open-source NLP datasets specific to natural language processing. Wikipedia Links Data: With around 13 million documents and corresponding hyperlinks, this massive NLP dataset treats each page as an entity. Penn Treebank: The corpus was taken from the Wall Street Journal and remains one of the most popular sets for the evaluation of sequence labeling models.


Voice AI Predictions for 2022 from 25 Industry Leaders - Voicebot.ai

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How will voice AI develop in 2022? More than 25 voice industry pros offer your predictions for the coming year. There will be more enterprise focus as a continuing trend of 2021, more custom assistants, and several new developments related to the metaverse. This past year was an important transition year for the voice AI market as Brandon Kaplan and Pete Erickson aptly highlight. Consumer applications and the general-purpose consumer assistants from the tech giants drove interest in the market for many years, but that changed in 2021 as enterprise use cases and customer, brand-owned assistants took center stage.


The Top Voice AI Stories of 2021 - Voicebot.ai

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Looking back at 2021 it was a different kind of year for voice AI than in the past. We could have said that in 2020 as well, but that was true on every societal and economic level due to the pandemic. However, we saw the seeds of change in the voice AI industry in late 2019 that was paused briefly and then accelerated in 2020 which set up 2021 to be the year of enterprise adoption. Voice AI news, innovation, and investment were largely driven by consumer applications in the period 2016 – 2019. Amazon, Google, and Apple (and occasionally Samsung) dominated the headlines related to the technology.


Global Big Data Conference

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The voice recognition market is under continued market growth and is expected to reach USD $27.155 billion by 2026, at a CAGR of 16.8% over the forecast period 2021 - 2026, according to Mordor Intelligence. Voice and speech recognition is technology that assists in receiving and interpreting the human voice and carrying out spoken commands. This type of technology is widely increasing in access to mobile devices and other consumer electronics due to improvements from a variety of capabilities from network improvements, data storage, open API integrations and most notably from Artificial Intelligence. With the rising use of artificial intelligence (AI) and virtual assistants, such as Apple Siri, Amazon Alexa, Google Assistant, new voice and audio solutions like Clubhouse plus the increased use of online collaboration software like Microsoft Teams, Zoom or Cisco's Webex, the demand for speech recognition software is accelerating. And we cannot forget about the agile innovators like TikTok, that is a video-focused social networking service owned by Chinese company ByteDance.


Master Artificial Intelligence

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Welcome to the comprehensive course on Master Artificial Intelligence Step-by-Step Guide for 2021. R Tutor is a team of software applications training professionals who explain complex information in the simplest form with relevant examples. Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. Artificial Intelligence can provide humans a great relief from doing various repetitive tasks.


A Market to Harness: Speech Recognition Artificial Intelligence (AI) Innovations On The Rise

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The voice recognition market is under continued market growth and is expected to reach USD 27.155 billion by 2026, at a CAGR of 16.8% over the forecast period 2021 - 2026, according to Mordor Intelligence. Voice and speech recognition is technology that assists in receiving and interpreting the human voice and carrying out spoken commands. This type of technology is widely increasing in access to mobile devices and other consumer electronics due to improvements from a variety of capabilities from network improvements, data storage, open API integrations and most notably from Artificial Intelligence. With the rising use of artificial intelligence (AI) and virtual assistants, such as Apple Siri, Amazon Alexa, Google Assistant, new voice and audio solutions like Clubhouse plus the increased use of online collaboration software like Microsoft Teams, Zoom or Cisco's Webex, the demand for speech recognition software is accelerating. And we cannot forget about the agile innovators like TikTok, that is a video-focused social networking service owned by Chinese company ByteDance.


ASRU: Integrating speech recognition and language understanding

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Jimmy Kunzmann, a senior manager for applied science with Alexa AI, is one of the sponsorship chairs at this year's IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). His research team also presented two papers at the conference, both on the topic of "signal-to-interpretation", or the integration of automatic speech recognition and natural-language understanding into a single machine learning model. "Signal-to-interpretation derives the domain, intent, and slot values directly from the audio signal, and it's becoming more and more a hot topic in research land," Kunzmann says. "Research is driven largely by what algorithm gives the best performance in terms of accuracy, and signal-to-interpretation can drive accuracy up and latency and memory footprint down." The Alexa AI team is constantly working to improve Alexa's accuracy, but its interest in signal-to-interpretation stemmed from the need to ensure Alexa's availability on resource-constrained devices with intermittent Internet connections.


Azure AI empowers organizations to serve users in more than 100 languages

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Microsoft announced today that 12 new languages and dialects have been added to Translator. These additions mean that the service can now translate between more than 100 languages and dialects, making information in text and documents accessible to 5.66 billion people worldwide. "One hundred languages is a good milestone for us to achieve our ambition for everyone to be able to communicate regardless of the language they speak," said Xuedong Huang, Microsoft technical fellow and Azure AI chief technology officer. Translator today covers the world's most spoken languages including English, Chinese, Hindi, Arabic and Spanish. In recent years, advances in AI technology have allowed the company to grow its language library with low-resource and endangered languages, such as Inuktitut, a dialect of Inuktut that is spoken by about 40,000 Inuit in Canada.