"Automatic speech recognition (ASR) is one of the fastest growing and commercially most promising applications of natural language technology. Speech is the most natural communicative medium for humans in many situations, including applications such as giving dictation; querying database or information-retrieval systems; or generally giving commands to a computer or other device, especially in environments where keyboard input is awkward or impossible (for example, because one's hands are required for other tasks)."
– from Linguistic Knowledge and Empirical Methods in Speech Recognition. By Andreas Stolcke. (1997). AI Magazine 18 (4): 25-32.
Today marked the kickoff of Xiaomi's annual Mi Developer conference in Beijing, and the tech giant wasted no time in announcing updates across its AI portfolio. It took the wraps off the latest release of Mobile AI Compute Engine (MACE), its open source machine learning framework, and it demoed an improved version of its Xiao AI voice assistant (Xiao AI 3.0). Xiao AI, which Xiaomi says is used by 49.9 million users each month, will soon support multi-turn conversations à la Alexa Conversations and Google's Continued Conversation. This will be enabled on select phones, including the Xiaomi Mi 9 Pro and the Xiaomi Mi 9 via a software update, and it will allow for interruptions of the assistant at any time with new requests or commands. Xiao AI 3.0 also boasts improved voice shortcut functionality and a voice reply feature that will let users respond to incoming calls with transcribed text messages.
Ever since the advent of mankind, humans have tried to make living easier on the face of the earth. It was because of this search for ease that has led us to the three industrial revolutions. Today, we are approaching fast towards fourth industrial revolution and it is all because of Artificial Intelligence and Machine Learning. Machine Learning algorithms have enabled the invention and development of intelligent software. These intelligent software, machines and robots have made both business and domestic life better.
This is an exciting opportunity to shape the future of voice interaction at Dyson. Working within a small team you will be responsible for building the software framework to enable rapid prototyping and development of voice control and dialogue systems. Your goal will be to implement the functionality of the latest API's for Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) across embedded and cloud platforms. You will use your deep understanding and experience to determine the software and hardware architecture for voice control applications on our next generation products.
According to the World Health Organization, 1 billion people on Earth have some form of disability. It's not surprising, then, that Microsoft's AI for Good campaign supports efforts that drive accessibility, empowering people to achieve more, regardless of their level of ability. AI for Good is a $50 million commitment from Microsoft to enable innovators to create solutions that leverage artificial intelligence (AI) technologies. The support includes use of Microsoft's Azure cloud and AI tools. AI can serve as the'brains' behind tools that enhance independence and productivity for people who have disabilities.
Intel's Nervana NNP-I chips are designed to be crammed into data centers for AI tasks like translating text or analyzing photos. It may not be obvious, but you're almost certainly using AI every day. Artificial intelligence-boosting hardware in your phone enables voice recognition and spots your friends in photos. In the cloud, it delivers search results and weeds out spam email. Next up for dedicated AI hardware will be your laptop, Intel expects.
Researchers have come up with a new attack strategy against smart assistants. These attacks threaten all devices featuring voice assistants. Dubbed as'LightCommands', these attacks enable a potential attacker to inject voice commands to the devices and take control of them. Researchers have developed new attacks that allow meddling with smart assistants. These attacks named'LightCommands' allow injecting audio signals to voice assistants.
A self-driving car approaches a stop sign, but instead of slowing down, it accelerates into the busy intersection. An accident report later reveals that four small rectangles had been stuck to the face of the sign. These fooled the car's onboard artificial intelligence (AI) into misreading the word'stop' as'speed limit 45'. There are instances of deceiving facial recognition systems by sticking a printed pattern on glasses or hats and tricking speech recognition systems using white noise. AI is part of daily life, running everything from automated telephone systems to user recommendations on the streaming service Netflix.
Automatic speech recognition, or ASR, is a foundational part of not only assistants like Apple's Siri, but dictation software such as Nuance's Dragon and customer support platforms like Google's Contact Center AI. It's the thing that enables machines to parse utterances for key phrases and words and that allows them to distinguish people by their intonations and pitches. Perhaps it goes without saying that ASR is an intense area of study for Facebook, whose conversational tech is used to power Portal's speech recognition and who is broadening the use of AI to classify content on its platform. To this end, at the InterSpeech conference earlier this year the Menlo Park company detailed wave2vec, a novel machine learning algorithm that improves ASR accuracy by using raw, untranscribed audio as training data. Facebook claims it achieves state-of-the-art results on a popular benchmark while using two orders of magnitude less training data and that it demonstrates a 22% error reduction over the leading character-based speech recognition system, Deep Speech 2. Wav2vec was made available earlier this year as an extension to the open source modeling toolkit fairseq, and Facebook says it plans to use wav2vec to provide better audio data representations for keyword spotting and acoustic event detection.
A typical after-work scene at my house goes something like this. She chimes, then lights up. My husband says the persistent disconnect between me and Alexa is my fault--I need to pause more, speak more clearly, and maybe throw in a "please" now and then. But not long after she moved in--a necessary sidekick, I was told, to the new sound system he had installed--I started getting the feeling she preferred Bob over me, no matter how polite I was (although often I wasn't). Once she started piping up every time someone in the house called my name ("Alyssa!"),
Imagine a world where medicine is made more precise with the aid of holograms, allowing doctors to digitally "see" into a patient's body during a procedure. A world where you can give a keynote address in perfect Japanese, in your own voice, anywhere, at any time--even if you don't speak Japanese. This may sound like the stuff of some far-away future, but in the 2019 SES Dean's Lecture Series, hosted by dean Jean Zu on October 17, Dr. Xuedong Huang assured an audience of more than 200 faculty, students, and staff that "All of these technologies exist today. Sponsored by the Schaefer School of Engineering and Science at Stevens Institute of Technology, Huang's enthralling lecture--"Breaking Human Interaction Barriers--AI, HoloLens and Beyond"--revealed a future enriched by artificial intelligence. Huang, a Microsoft Technical Fellow in Microsoft Cloud and AI, founded the company's speech technology group in 1993. This group brought speech recognition to the mass market with the ...