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Speech Recognition


DOUB's SpeechEMR uses AI to make medical transcription accurate and automated - IntelligentHQ

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Seoul, South Korea: SpeechEMR, an automatic voice recognition service designed by Seoul-based health-tech startup DOUB, records medical events and converts them into text data in real-time facilitating users to record medical events in a jiffy. SpeechEMR provides a high recognition rate of over 95 percent using artificial intelligence (AI) voice recognition technology specially designed for use in the medical field. Spoken audio data such as the conversations between doctors and patients or medical dictations are converted into text in real-time, through processes such as noise removal and silent syllable separation. This voice recognition service then quickly edits and saves the medical records with misspelling and omission on display coupled with correct word suggestions and medical terminology dictionary provision. Preventing information errors and improving the clarity highlights important information such as numbers, dates, units, sizes, and locations increasing the clarity and preventing sensitive information errors.


Microsoft buys AI speech tech company Nuance for $19.7 billion

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Microsoft is buying AI speech tech firm Nuance for $19.7 billion, bolstering the Redmond, Washington-based tech giant's prowess in voice recognition and giving it further leverage in the health care market, where Nuance sells many products. Microsoft will pay $56 per share for Nuance, a 23 percent premium over the company's closing price last Friday. The deal includes Nuance's net debt. Nuance is best known for its Dragon software, which uses deep learning to transcribe speech and improves its accuracy over time by adapting to a user's voice. Nuance has licensed this tech for many services and applications, including, most famously, Apple's digital assistant Siri.


Microsoft buying speech recognition firm Nuance in $16B deal

Boston Herald

Microsoft, on an accelerated growth push, is buying speech recognition company Nuance in a deal worth about $16 billion. The acquisition will get Microsoft deeper into hospitals and the health care industry through Nuance's widely used medical dictation and transcription tools. Microsoft will pay $56 per share cash. The companies value the transaction including debt at $19.7 billion. Shares of Burlington, Mass.-based Nuance surged more than 16% in Monday trading.


Spotify's voice-controlled 'Car Thing' is available for some subscribers

Engadget

At this point, we've seen rumors, job listings, blog posts, FCC filings and more rumors about Spotify's in-car music player over the span of a few years. In fact, I was convinced it would never become a thing the public could actually use. When the company first revealed a piece of hardware called "Car Thing" in 2019, Spotify was clear the test was meant "to help us learn more about how people listen to music and podcasts." It also explained that there weren't "any current plans" to make that device available to consumers. Now Spotify is ready for select users to get their hands on a refined version of the voice-controlled in-car player.


Microsoft Makes a $16 Billion Entry Into Health Care AI

WIRED

When Microsoft CEO Satya Nadella spoke to investors Monday about his company's plan to acquire speech-recognition specialist Nuance for $16 billion, he emphasized the importance of artificial intelligence in health care. Nuance's software listens to doctor-patient conversations and transcribes speech into organized digitized medical notes. This helps explain the hefty price tag, even as voice recognition has become commoditized and now comes packaged with every smartphone and laptop. But Microsoft may also see much broader potential for Nuance's technology. Gregg Pessin, an analyst with Gartner, says the deal gives Microsoft "an entry point into the health care industry, and a huge customer base already running this stuff."


Microsoft's Nuance Gambit Shows Healthcare Is Next Tech Battleground

WSJ.com: WSJD - Technology

Microsoft Corp.'s $16 billion deal for Nuance Communications Inc. is the latest sign that the next battleground for technology giants will be in healthcare, an industry whose need to embrace data and software was underscored by the pandemic. The acquisition will help Microsoft tap into Nuance's big business selling its software to healthcare systems, according to analysts and healthcare executives. Speech-recognition software like that developed by Nuance is emerging as an important new opportunity in medicine as doctors seek to speed up documentation of patient work with dictation rather than getting bogged down taking notes, executives said. "This coming together is about empowering healthcare," Satya Nadella, Microsoft's chief executive, said in an investor call. "It's now very clear that healthcare organizations that accelerate their digital investments can improve patient outcomes and reduce cost at scale."


Spotify rolls out its own hands-free voice assistant on iOS and Android

Engadget

Spotify users on iOS and Android have another way to quickly play something. The audio streaming service has an in-app voice assistant you can operate hands free, building on the existing voice search function. After saying the "Hey, Spotify" wake word, you can ask the app to fire up a song or playlist or play music from a certain artist. You'll need to grant Spotify permission to access your microphone if you want to use the feature, which you can switch on from the voice interactions section of the menu. As GSM Arena notes, Spotify's privacy policy states that the service only stores recordings and transcriptions of your searches after you say the wake word or tap the voice button.


Study finds that even the best speech recognition systems exhibit bias

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Even state-of-the-art automatic speech recognition (ASR) algorithms struggle to recognize the accents of people from certain regions of the world. That's the top-line finding of a new study published by researchers at the University of Amsterdam, the Netherlands Cancer Institute, and the Delft University of Technology, which found that an ASR system for the Dutch language recognized speakers of specific age groups, genders, and countries of origin better than others. Speech recognition has come a long way since IBM's Shoebox machine and Worlds of Wonder's Julie doll. But despite progress made possible by AI, voice recognition systems today are at best imperfect -- and at worst discriminatory. In a study commissioned by the Washington Post, popular smart speakers made by Google and Amazon were 30% less likely to understand non-American accents than those of native-born users.


Even the Best Speech Recognition Systems Exhibit Bias, Study Finds - Slashdot

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An anonymous reader quotes a report from VentureBeat: Even state-of-the-art automatic speech recognition (ASR) algorithms struggle to recognize the accents of people from certain regions of the world. That's the top-line finding of a new study published by researchers at the University of Amsterdam, the Netherlands Cancer Institute, and the Delft University of Technology, which found that an ASR system for the Dutch language recognized speakers of specific age groups, genders, and countries of origin better than others. The coauthors of this latest research set out to investigate how well an ASR system for Dutch recognizes speech from different groups of speakers. In a series of experiments, they observed whether the ASR system could contend with diversity in speech along the dimensions of gender, age, and accent. The researchers began by having an ASR system ingest sample data from CGN, an annotated corpus used to train AI language models to recognize the Dutch language.


Tiny machine learning brings AI to IoT devices - EDN

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One advantage that the IoT brought to design was the ability for a small local device to access the network's virtually-unlimited computing power. The Amazon Echo is a classic example: a low-cost local device that provided powerful speech recognition AI and an immense application library by way of its Internet connection. Now, some of that AI is moving into the local device to help minimize bandwidth and latency concerns by employing an efficient form of machine learning (ML) for smaller devices. An example of what can be accomplished by placing AI in edge devices can be found in the article AI helps turn gas sensor into electronic nose. In this instance the ML that generates the sensor's algorithms takes place during the design cycle, and the local device simply runs the algorithm.