Speech Recognition

Technology companies of all sizes and in locations all around the world are developing AI-driven products aimed at reducing operating costs, improving decision-making and enhancing consumer services across a range of client industries. The sum of these drivers -- new programming techniques, more data and faster chips -- has seen AI converge with human-level performance in the key areas of image classification and speech recognition over recent years (see EXHIBIT 2). Chipmakers stand to benefit from increased demand for processing power, particularly makers of graphical processing units for AI program training. And internet companies with AI at the core of their consumer services (such as digital assistants and new software features) stand to benefit directly from improvements in speech recognition and image classification.

All large companies are investing in voice recognition and the world is slowly yet steadily adjusting to the new technology of Artificial intelligence. So why is it taking so long, why isn't it part of our day to day lives yet? Here are the 6 Reasons why. You go to a store to look for a particular colour and brand of a product. You ask an employee if the product you want is available. The employee goes to the warehouse, checks his inventory for the product, and comes back a while later, only to tell you that your product isn't available anymore. Now imagine this, you enter the same store and tell a tiny device the product you want to buy. Within a second, a voice tells you the exact availability of your product, and, if unavailable, gives you details on the outlets where the product is available. The AI device does this by internally scanning through all the digital inventory systems. With numerous benefits in relation to cost logistics and more importantly convenience, why hasn't the art of speech recognition and personal assistants been perfected yet? With science making huge strides in sound wave recognition, we take a look at some of the main problems researchers are facing when decoding speech to text. Noise Voice recording machines detect sound waves that are generated through speech.

Until your phone or tablet is set up just the way you want it, a brand new device feels kind of foreign. With the V30, LG is giving you more options for making the phone your own. You can match haptic feedback to the ringtone of your choosing, for starters. From the manual shooting mode, you can access Graphy, a sort of photo editing suite that grants access to editing presets designed by pro photographers.

That's part of the reason Google has been updating Gboard for Android with voice support for more international languages, working with native speakers to train machine learning models. Today, Google announced that it's supporting an additional 20 languages and also adding English dialects for four African countries. This means language support for a total of 30 new international locations, mostly centered on the Indian subcontinent and Africa. In total, this brings the grand total of Gboard's voice recognition to 119 languages.

Even the most traditional of British institutions are using AI to enrich the consumer experience, with Wimbledon using IBM Watson to create a voice assistant called Fred (after Fred Perry, obviously) to direct fans to the nearest strawberries. Consumer trust in Artificial Intelligence is growing, and adoption around the world is rocketing - but we must make sure that as trust in this kind of technology grows, accountability comes with it. Voice recognition software makes multiple solutions accessible to people with sight impairments, as well as those with dyslexia and limited mobility. But for any jobs that AI is going to replace, its existence will also evolve existing jobs and create new ones.

Developer of human-machine interaction technologies using artificial intelligence designed to develop speech recognition system, semantic analysis and vertical search technologies. Developer of cloud-based security software designed to detect mobile threats and improve mobile security. The company's cloud-based security software protects mobile phones from viruses, malware, spyware and has the ability to back up and restore data and tools to help locate lost or stolen phones by using machine intelligence to detect threats, enabling users to secure their personal information and data that are stored in mobile devices from serious cyber attacks. It applies artificial intelligence, algorithmic science and machine learning to cyber security and improve the way companies, governments and end users proactively solve security problems.

Adam Coates is the Director of Baidu's Silicon Valley AI Lab - http://research.baidu.com

Now, our web browsers will become familiar with to Web Speech API, which allows users to integrate voice data in web apps. With the Web Speech API, we can develop rich web applications with natural user interactions and minimal visual interface, using voice commands. By establishing a socket connection between the client and server, our chat messages will be passed back and forth between the browser and our server, as soon as text data is returned by the Web Speech API (the voice message) or by API.AI API (the "AI" message). Once the connection is established and the message is received, use the API.AI APIs to retrieve a reply to the user's message: When API.AI returns the result, use Socket.IO's socket.emit() to send it back to the browser.

Meanwhile, water scarcity and draughts present serious problems, which AI can help solve through specific voice-activated devices enabling irrigation or dyke management at a distance. IoT enables vehicle to vehicle communications (V2V), allowing cars to communicate with one another and making the whole driving experience a lot safer. Moreover AI-powered park assistants support drivers while parking and help avoid collision, whereas environmental sensors detect environment conditions, thus adapting headlights levels or adapting windscreen wipers to them. To find out more about the future of Artificial Intelligence, Machine Learning and Internet of Things in specific industries, please visit our website.

In this world, the bot-to-bot business model will be something ordinary and it is going to be populated by two types of bots: master bots and follower bots. This would result in some players creating "universal" bots (master bots) which everyone else will use as gateways for their (peripheral) interfaces and applications. Google has recently created a "Neural Machine Translation", a relevant leap ahead in the field, with the new version even enabling zero-short translation (in languages which they were not trained for). This was not originally intended to part of this article, but I found useful to go quickly through main players in the space in order to understand the importance of speech recognition in business contexts.