Collaborating Authors


MIT PixelPlayer "Sees" Where Sounds Are Coming From


The "cocktail party effect" describes humans' ability to hold a conversation in a noisy environment by listening to what their conversation partner is saying while filtering out other chatter, music, ambient noises, etc. We do it naturally but the problem has been widely studied in machine learning, where the development of environmental sound recognition and source separation techniques that can tune into a single sound and filter out all others is a research focus. MIT CSAIL researchers recently introduced their PixelPlayer system, which has learned to identify objects that produce sound in videos. The system uses deep learning and was trained by binge-watching 60 hours of musical performances to identify the natural synchronization of visual and audio information. The team trained deep neural networks to concentrate on images and audio and identify pixel-level image locations for sound sources in the videos.

How is Artificial Intelligence (AI) Making TikTok Tick?


Being the hot new trend for the youth and teenagers while prompting raised eyebrows from the adult section of the populace, TikTok, the video-sharing app which lets it's users create and share 15-second videos on an array of topics, has taken the digital world by storm and became the social network hub for amateur music videos. Tik Tok is an app which enables its users, largely the youth, to fulfil and satisfy their fun buried desires by creating an assortment of videos ranging from various fun challenges to dance to magic tricks to funny videos. What started as an app acclaimed and known for its lip-syncing feature, restricted to various areas of Asia, soon gave way to the merry world of dancing, gymnastics, cheerleading, parkour, and comedy, now finding its place and creating a buzz in various parts of the world. The app is known widely for its act-out memes, accompanied by music and other sound clips which get incessantly reproduced and remixed among its users. It's got a varied collection of tunes be it pop, rap, R&B, electro, and DJ tracks, which accompany its 15-second video clips, backed by a wide mixture of effects and filters.

Google Assistant recommends your YouTube Music on Nest speakers


Over the last couple of years, Google has gradually improved YouTube Music with features like playback screen lyrics and an Explore tab. Now, it has unveiled integration with some of its other products, including Android TV, Google Maps and and Google Assistant. The first feature is recommendations via Google Assistant. To use it, you simply say: "Hey Google, play recommended music from YouTube Music," and you'll get personalized music suggestions, including favorite artists and genres, based on your listening history. Unfortunately, this feature is only available on newer Nest speakers and not Google Home devices.

Amazon's bestselling smart speaker, the 3rd Gen Echo Dot is now under £30

Daily Mail - Science & tech

Amazon's bestselling and most popular smart speaker, the 3rd generation Echo Dot with Alexa voice control is a must-have smart device for any home. And with a current saving of 40 per cent (£20), this is an incredible deal that shouldn't be missed. Now just £29.99, the Echo Dot can stream songs, set timers and connect with other Amazon devices. It can also track fitness, answer questions, and allow you to voice control your home. Simply plug in, connect to wifi, and the Alexa smart speaker is ready to go.

Muru Music looks to launch AI music therapy platform


At first glance, Muru Music Health comes across as another digital music streaming platform. But according to founder Nicc Johnson, the digital platform has been designed specifically to tailor the listening experience to a person's music tastes. "What streaming services today do really well is they look at the aggregate of user data -- of millions of users -- and they find patterns to be able to recommend music to you. Collaborative filtering in a nutshell," he said. "The difference here is we are looking at the individual, and we're looking specifically for music to help them relax, exercise, or trigger positive memories. That means we can't really rely on music listening of another user because it doesn't have the same affects."

The best smart speakers for all budgets

The Guardian

After almost six years on the market, smart speakers now come in a variety of sizes, shapes, capabilities and prices. Whether you want a cheap speaker to keep the kids entertained, one that doubles as a digital photo frame or one that sounds so good you'll want to yell "turn it up to 11", here's a quick guide to the best on the market. Google's Assistant is the best voice system on the market. It has better understanding than rivals, an enormous range of knowledge and – importantly – the ability to choose between male and female voices, even on a user-by-user basis as Google can distinguish between the individuals giving instructions. The Nest Mini is the second generation of Google's smallest and cheapest smart speaker.

How to play your personal music collection on Google Home and Chromecast


Google Play Music is currently the best streaming music service for people who have their own music collections. The service lets users upload 50,000 of their own music files, then access the audio on a wide range of streaming devices. It's a great way to access your own music files from anywhere, and it doesn't cost a dime. Unfortunately, the free ride is just about over. At the end of this year, Google will discontinue Google Play Music and push users over to YouTube Music as a replacement.

Using Machine Learning to Analyze Taylor Swift's Lyrics


For the past few months, the Curriculum team at Codecademy has been hard at work creating Machine Learning courses. While we all loved writing the courses, we also wanted to see what we could do with real-world data. As a result, we challenged each other to find a use for machine learning in a topic that we were passionate about. It's said that popular music is a reflection of society, a barometer for our collective wants, fears, and emotional states. Others are of the belief that music is more a reflection of the artist, a diary that's been flung from the nightstand drawer into the media frenzy of our modern world.

Researchers' AI system infers music from silent videos of musicians


In a study accepted to the upcoming 2020 European Conference on Computer Vision, MIT and MIT-IBM Watson AI Lab researchers describe an AI system -- Foley Music -- that can generate "plausible" music from silent videos of musicians playing instruments. They say it works on a variety of music performances and outperforms "several" existing systems in generating music that's pleasant to listen to. It's the researchers' belief an AI model that can infer music from body movements could serve as the foundation for a range of applications, from adding sound effects to videos automatically to creating immersive experiences in virtual reality. Studies from cognitive psychology suggest humans possess this skill -- even young children report that what they hear is influenced by the signals they receive from seeing a person speak, for example. Foley Music extracts 2D key points of people's bodies (25 total points) and fingers (21 points) from video frames as intermediate visual representations, which it uses to model body and hand movements.

How WWII Was Won, and Why CS Students Feel Unappreciated

Communications of the ACM

Observations of the 75th anniversary of the end of World War II in Europe (May 8, 1945) included remembrances of such searing events as the struggle on Omaha Beach on D-Day, the Battle of the Bulge, and at least some recognition of the enormous contribution made by the Russian people to the defeat of Fascism. Yet in all this, I suspect the role of the first "high-performance computing" capabilities of the Allies--known as Ultra in Britain, Magic in the U.S.--will receive too little attention. The truth of the matter is that the ability to hack into Axis communications made possible many Allied successes in the field, at sea, and in the air. Alan Turing and other "boffins" at Britain's Bletchley Park facility built the machine--a much-improved version of a prototype developed by the Poles in the interwar period--that had sufficient computing power to break the German Enigma encoding system developed by Arthur Scherbius. The Enigma machine was a typewriter-like device with three rotors, each with an alphabet of its own, so each keystroke could create 17,576 possible meanings (26 x 26 x 26).