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Computational model decodes speech by predicting it


UNIGE scientists developed a neuro-computer model which helps explain how the brain identifies syllables in natural speech. The model uses the equivalent of neuronal oscillations produced by brain activity to process the continuous sound flow of connected speech. The model functions according to a theory known as predictive coding, whereby the brain optimizes perception by constantly trying to predict the sensory signals based on candidate hypotheses (syllables in this model).

How To Build A Speech Recognition Bot With Python


You may have realized something now. The overwhelming success of speech-enabled products like Amazon Alexa has proven that some degree of speech support will be an essential aspect of household technology for the foreseeable future. In other words, speech-enabled products would be a game changer as that offer a level of interactivity and accessibility that few technologies can match. Check out what books helped 20 successful data scientists grow in their career. Speed is a big reason voice is poised to become the next major user interface.

Text to Speech Technology: How Voice Computing is Building a More Accessible World


In a world where new technology emerges at exponential rates, and our daily lives are increasingly mediated by speakers and sound waves, text to speech technology is the latest force evolving the way we communicate. Text to speech technology refers to a field of computer science that enables the conversion of language text into audible speech. Also known as voice computing, text to speech (TTS) often involves building a database of recorded human speech to train a computer to produce sound waves that resemble the natural sound of a human speaking. This process is called speech synthesis. The technology is trailblazing and major breakthroughs in the field occur regularly.

Machines That Can Understand Human Speech: The Conversational Pattern Of AI


Early on in the evolution of artificial intelligence, researchers realized the power and possibility of machines that are able to understand the meaning and nuances of human speech. Conversation and human language is a particularly challenging area for computers, since words and communication is not precise. Human language is filled with nuance, context, cultural and societal depth, and imprecision that can lead to a wide range of interpretations. If computers can understand what we mean when we talk, and then communicate back to us in a way we can understand, then clearly we've accomplished a goal of artificial intelligence. This particular application of AI is so profound that it makes up one of the fundamental seven patterns of AI: the conversation and human interaction pattern.

Natural Language Principles


Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language. NLP draws from many disciplines, including computer science and computational linguistics, in its pursuit to fill the gap between human communication and computer understanding. While natural language processing isn't a new science, the technology is rapidly advancing thanks to an increased interest in human-to-machine communications, plus an availability of big data, powerful computing and enhanced algorithms. As a human, you may speak and write in English, Spanish or Chinese. But a computer's native language -- known as machine code or machine language -- is largely incomprehensible to most people.

Speech Recognition A-Z with Hands-on


The Speech Recognition course gives you a detailed look at the science of applying machine learning algorithms to process large amounts of speech data. Speech recognition is driving the growth of the AI market, and this course helps you develop the skills required to become an Speech recognition professional. The Speech Recognition course gives you a detailed look at the science of applying machine learning algorithms to process large amounts of speech data. Speech recognition is driving the growth of the AI market, and this course helps you develop the skills required to become a Speech recognition professional. This course has been aligned with industry best practices as it has been created by industry leaders.

Usage of speaker embeddings for more inclusive speech-to-text


English is one of the most widely used languages worldwide, with approximately 1.2 billion speakers. In order to maximise the performance of speech-to-text systems it is vital to build them in a way that recognises different accents. Recently, spoken dialogue systems have been incorporated into various devices such as smartphones, call services, and navigation systems. These intelligent agents can assist users in performing daily tasks such as booking tickets, setting-up calendar items, or finding restaurants via spoken interaction. They have the potential to be more widely used in a vast range of applications in the future, especially in the education, government, healthcare, and entertainment sectors.

Clinical Voice Assistant Startup Suki Looks Beyond Healthcare, Debuts Upgraded AI Platform -


Clinical voice assistant developer Suki has created a new voice platform with improved artificial intelligence. The Suki Speech Service, referred to by the company as S3, makes Suki's voice assistant faster, more accurate, and flexible enough that it could be used by professionals outside of the healthcare sector. Suki's current voice assistant is built to reduce the amount of time and energy doctors spend on administrative tasks and records. The voice assistant records, transcribes, and organizes a doctor's conversations with a patients and any notes on the case. Suki can then automatically complete the data entry necessary for Electronic Health Records (EHR).

Google updates its Nest Hub Max to support group calling

USATODAY - Tech Top Stories

Google is making it easier to connect with more people in video calls and meetings using its Nest Hub Max video display device. The Nest Hub Max ($229), released about 10 months ago, served as Google's entry in the smart video display competition with Amazon's Echo Show and Facebook's Portal. An update, out now, lets you make group calls of up to 32 with the Google Duo app – and up to 100 in the Google Meet app. Previously, Nest Hub Max get-togethers maxed out at person to person calls using Google Duo. You create your groups in the Google Duo app (available for Android and iOS) and then tell the Hub Max, "Hey, Google, make a group call."

Echo Auto: Amazon releases Alexa voice assistant for your car

The Independent - Tech

Amazon has released its first Echo device for use outside of the house, allowing users to take Alexa in their car. The company revealed the device in 2018 but it has finally come to customers in the UK and Ireland. Echo Auto plugs into a car's 12V power outlet or built-in USB port and connects to the in-car stereo via either audio jack cable or Bluetooth to enable the use of voice assistant Alexa inside the vehicle. Users are then able to use Alexa voice commands to control music, check the news, make phone calls or check their schedule without taking hands off the wheel or eyes off the road. The device gets internet connectivity by connecting to a user's smartphone and the Alexa app and using its existing data plan.