  Query by Singing/Humming (QBSH) is a Music Information Retrieval (MIR) system
with small audio excerpt as query. The rising availability of digital music
stipulates effective music retrieval methods. Further, MIR systems support
content based searching for music and requires no musical acquaintance. Current
work on QBSH focuses mainly on melody features such as pitch, rhythm, note
etc., size of databases, response time, score matching and search algorithms.
Even though a variety of QBSH techniques are proposed, there is a dearth of
work to analyze QBSH through query excerption. Here, we present an analysis
that works on QBSH through query excerpt. To substantiate a series of
experiments are conducted with the help of Mel-Frequency Cepstral Coefficients
(MFCC), Linear Predictive Coefficients (LPC) and Linear Predictive Cepstral
Coefficients (LPCC) to portray the robustness of the knowledge representation.
Proposed experiments attempt to reveal that retrieval performance as well as
precision diminishes in the snail phase with the growing database size.
