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Sunny Leone to Feature in a Canadian Producer’s Music Video

Mumbai, May 11 : Indo-Canadian actress Sunny Leone has joined forces with Canadian producer and DJ of Indian descent, UpsideDown, for the video of the song "Got it all".

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The music video has been executive produced by Urban Asian Music and promoted by 360 Worldwide.
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Mumbai, May 11 : Indo-Canadian actress Sunny Leone has joined forces with Canadian producer and DJ of Indian descent, UpsideDown, for the video of the song “Got it all”.

It also features The PropheC, a Canadian singer-songwriter of Indian descent.

“We continue to push the boundaries of music by incorporating our culture and with the help of like-minded creatives. I’m grateful we are turning our dreams into reality,” UpsideDown, known for hits like Mickey Singh’s “Phone” and Jasmin Walia’s “Temple”, said in a statement.

UpsideDown and The PropheC take on the role of handymen in their music video who head to work at Sunny's mansion.
Sunny Leone with UpsideDown, BollywoodCountry

The PropheC believes UpsideDown has created his own lane in terms of production and “I am proud to be apart of it and continue to push our boundaries”.

UpsideDown and The PropheC take on the role of handymen in their music video who head to work at Sunny’s mansion.

Also Read: Indian Art Forms in International Festivals Through Sands of Culture Series

Sunny said: “UpsideDown and The PropheC were great to work with. It’s an exciting time for North American Punjabi music.”

The music video has been executive produced by Urban Asian Music and promoted by 360 Worldwide. (BollywoodCountry)

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Google AI can focus on individual speakers in a crowd

The visual signal not only improves the speech separation quality significantly in cases of mixed speech, but, importantly, it also associates the separated, clean speech tracks

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Google india launches 'Tz' to help people pay their utility bills. Wikimedia Commons
Google AI to identify speakers from crowd. Wikimedia Commons

Just as most smartphone cameras now allow users to focus on a single object among many, it may soon be possible to pick out individual voices in a crowd by suppressing all other sounds, thanks to a new Artificial Intelligence (AI) system developed by Google researchers.

This is an important development as computers as not as good as humans at focusing their attention on a particular person in a noisy environment. Known as the cocktail party effect, the capability to mentally “mute” all other voices and sounds comes natural to us humans.

Google has collaborated with getty images. Wikimedia Commons
Google AI will identify individual speakers now. Wikimedia Commons

However, automatic speech separation — separating an audio signal into its individual speech sources — remains a significant challenge for computers, Inbar Mosseri and Oran Lang, software engineers at Google Research, wrote in a blog post this week. In a new paper, the researchers presented a deep learning audio-visual model for isolating a single speech signal from a mixture of sounds such as other voices and background noise.

“In this work, we are able to computationally produce videos in which speech of specific people is enhanced while all other sounds are suppressed,” Mosseri and Lang said. The method works on ordinary videos with a single audio track, and all that is required from the user is to select the face of the person in the video they want to hear, or to have such a person be selected algorithmically based on context.

Also Read: Want To Know What Facebook, Google Know About You?

The researchers believe this capability can have a wide range of applications, from speech enhancement and recognition in videos, through video conferencing, to improved hearing aids, especially in situations where there are multiple people speaking. “A unique aspect of our technique is in combining both the auditory and visual signals of an input video to separate the speech,” the researchers said.

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This will also help in speech enhancement . VOA

“Intuitively, movements of a person’s mouth, for example, should correlate with the sounds produced as that person is speaking, which in turn can help identify which parts of the audio correspond to that person,” they explained.

The visual signal not only improves the speech separation quality significantly in cases of mixed speech, but, importantly, it also associates the separated, clean speech tracks with the visible speakers in the video, the researchers said. IANS

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