Based on noise-resistant fingerprint comparison methods, SoundID from OPNS delivers content recognition that can generate broadcast playlists on any type of content, such as ad spots, music, jingles, fillers, interviews, and to produce related reports and statistics.
SoundID uses OPNS’ in-house algorithms and, according to the company, provides at least 99% recognition accuracy of fingerprinted source items inside broadcast streams.
The solution monitors and reports on any sound from radio, television, or any other input stream. It provides information on when and what was played, and can also tell the user if (and where) something was cut out of the original piece.
Available as either an on-premises tool or cloud-based solution, SoundID also provides content discovery by fingerprint pattern recurrences to detect any unknown content from competitor’s streams.
It also carries out audience measurement based on fingerprints dynamically generated on smartphones. This, the company says, means there is no privacy issue, no source modification, no dedicated hardware required and results in automatic data collection from a broad panel of radio listeners.
SoundID is based on a scale-out architecture and is suitable for both large and smaller broadcasters.
IBC Stand: 10.D41
