Fingerprinting or content based identification (CBID) technology work by extracting some unique piece of features/characteristics (often called fingerprint) from audio files and stores them in a database. When an unidentified piece of audio file is presented, fingerprint of that piece is calculated and matched against those which are stored in the database. Here, the research introduces factors that must be considered when performing a comparative evaluation of many fingerprinting algorithms, and presents a new evaluation framework that has been developed to address these factors. By using Chromaprint, Echoprint and Panako acoustic fingerprint algorithms, the research generates fingerprint of variable length audio section for each 300 audio songs and found that Panako is good choice than Echoprint and Chromaprint regarding audio matching queries. The queries were created with sections of audio with no modification as well as modifications like adding noise, recording, increase/decrease audio play speed, changing sampling rate and changing stereo sound to mono. This analysis gives the clear picture on which algorithm should be used to identify music queries recorded in different situations.