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Home | Tech | Just Hum To Search Songs On Google

Song stuck in your head? Just hum to search songs on Google 

The models are trained to identify songs based on a variety of sources, including humans singing, whistling or humming, as well as studio recordings.

By IANS
Updated On - 04:09 PM, Fri - 16 October 20
Song stuck in your head? Just hum to search songs on Google 

New Delhi: In a delight for music lovers, Google has announced a new capability where you can hum, whistle or sing a melody to find out the song that has been stuck in your head – no lyrics, artist name or perfect pitch required.

On your mobile device, open the latest version of the Google app or find your Google Search widget, tap the mic icon and say “what’s this song?” or click the “Search a song” button.
Then start humming for 10-15 seconds. On Google Assistant, it’s just as simple. Say “Hey Google, what’s this song?” and then hum the tune.

“This feature is currently available in English on iOS, and in more than 20 languages on Android. And we hope to expand this to more languages in the future,” Google announced during its virtual ‘Search On’ event on Thursday.

“After you’re finished humming, our machine learning algorithm helps identify potential song matches. And don’t worry, you don’t need perfect pitch to use this feature. We’ll show you the most likely options based on the tune,” said Krishna Kumar, Senior Product Manager, Google Search.

You can select the best match and explore information on the song and artist, view any accompanying music videos or listen to the song on your favourite music app, find the lyrics, read analysis and even check out other recordings of the song when available.

According to Google, a song’s melody is like its fingerprint. “We’ve built machine learning models that can match your hum, whistle or singing to the right fingerprint,” Kumar said.
When you hum a melody into Search, the machine learning models transform the audio into a number-based sequence representing the song’s melody.

The models are trained to identify songs based on a variety of sources, including humans singing, whistling or humming, as well as studio recordings.

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