![]() In the year 2000, the single “Naive Song” performed by Mirwais Ahmadzai from his album Production was the first ever track using Auto-Tune on the complete vocals. After the success of “Believe” the technique was initially referred to as the “Cher Effect”. In an early interview, the producers of “Believe” claimed they had used a DigiTech Talker FX pedal, in what Sound on Sound’s editors felt was an attempt to preserve a trade secret. While working with Cher on the song “Believe” in 1998, producers Mark Taylor and Brian Rawling discovered that if they set Auto-Tune on its most aggressive setting, so that it corrected the pitch at the exact moment it received the signal, the result was an unsettlingly robotic tone. Cher’s producers used the device to “exaggerate the artificiality of abrupt pitch correction”, contrary to its original purpose. Originally, Auto-Tune was designed to discreetly correct imprecise intonations, in order to make music more expressive, with the original patent asserting that “When voices or instruments are out of tune, the emotional qualities of the performance are lost.”Īccording to Chris Lee of the Los Angeles Times, Cher’s 1998 song “Believe” is “widely credited with injecting Auto-Tune’s mechanical modulations into pop consciousness”. Hildebrand had come up with the idea for a vocal pitch correction technology on the suggestion of a colleague’s wife, who had joked that she could benefit from a device to help her sing in tune. ![]() It was a trick - a mathematical trick.” Over several months in early 1996, he implemented the algorithm on a custom Macintosh computer, and presented the result at the NAMM Show later that year, where “it was instantly a massive hit.” Music industry engineers had previously considered the use of autocorrelation impractical because of the extremely large computational effort required, but Hildebrand found a “simplification changed a million multiply adds into just four. ![]() His method for detecting pitch involved the use of autocorrelation and proved to be superior to earlier attempts based on feature extraction that had problems processing certain aspects of the human voice such as diphthongs, leading to sound artifacts. research engineer specialized in stochastic estimation theory and digital signal processing.
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