Assessing the usability of Shazam mobile app

Like searching for a “needle” in a “haystack”, suppose that there is a large set of signals (finite sequences of numbers) fs1; s2; s3; g, and a special signal q that may or may not be in the collection. How can the signals be found in the collection that is similar, or identical to q, and how can this be done quickly? A solution to this question is the basis of the Shazam smart phone app, where a listener captures a short excerpt of a recorded song with the smart phone’s microphone, and in a matter of moments the app reports the name of the song and the artist. Here, the “needle” is the excerpt, and the “haystack” is a vast corpus of popular music. The Shazam algorithm is powered by Fourier analysis. This paper presents a report on a usability evaluation of Amazon Shazam app. The researchers present the outcome based on a task-based evaluation that involved 15 users of different level of experience who performed 5 tasks using the Shazam mobile app. Post-test questionnaire was used to capture users’ perceptions about the app. The results demonstrate that most of the participants were satisfied with services provided by the app.