SoundHound AI, Inc. is an audio and speech recognition company founded in 2005. It develops speech recognition, natural language understanding, sound recognition and search technologies. Its featured products include Houndify, a Voice AI developer platform, SoundHound Chat AI, a voice-enabled digital assistant, and music recognition mobile app SoundHound. The company’s headquarters are in Santa Clara, California.
The company was founded in 2005 by Keyvan Mohajer, an Iranian-Canadian computer scientist who had founded a number of dot com ventures before starting SoundHound.
In 2009, the company's Midomi app was rebranded as SoundHound but is still available as a web version on midomi.com.
In 2015, SoundHound became the first music recognition service shipping in autos, in a partnership with Hyundai, in the new Genesis model.
By May 2016, SoundHound had over 300 million users globally.
In 2018, SoundHound Inc. announced partnerships with Hyundai, Mercedes-Benz, and Honda to provide voice interaction for their products using its Houndify voice AI platform.
SoundHound won the 2020 Webby Award for Productivity (Voice) in the category Apps, Mobile & Voice.
On November 16 2021, SoundHound announced plans to become a public company via a SPAC merger with Archimedes Tech SPAC Partners Co. On April 28, 2022, the combined company SoundHound AI, Inc. went public, listed under the symbol SOUN on the Nasdaq. In 2022, the company laid off 10% of its staff and enforced salary cuts and it was reported that SoundHound raised less than half of what it originally projected in its SPAC merger deal. In April, 2023, SoundHound secured 100millioninstrategicfinancing.AccordingtoanarticleofJune2015SoundHoundInc.hadraisedatotalof40 million in funding from Global Catalyst Partners, Translink Capital, Walden Venture Capital, and other investors. This included 7millioninaSeriesBfundingroundthecompanysecuredinOctober2008,bringingtotalfundsraisedto12 million at that time.
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Music information retrieval (MIR) is the interdisciplinary science of retrieving information from music. Those involved in MIR may have a background in academic musicology, psychoacoustics, psychology, signal processing, informatics, machine learning, optical music recognition, computational intelligence or some combination of these. MIR is being used by businesses and academics to categorize, manipulate and even create music.