Nowadays, TV advertising is an important part of our daily life. However, it is usually hard for organizations that produce and pay for the advertisements to confirm whether their commercials are broadcasted as required in time and frequency. Consequently, a multimedia file search problem arises and it has drawn more and more attention in the past decade. In this thesis, we propose an automatic commercial search scheme using audio fingerprinting and implement it in a PC-based application. Our commercial search algorithm is composed of two parts: one for audio feature extraction and another for database search. For the first part, although the video stream of TV broadcast contains a great deal of intuitive information, we decide to ignore it because it takes much more storage and computations to process. For the audio stream, we have to extract proper audio features which can represent its characteristics and store them in a database for identification. We choose the Normalized Spectral Subband Centroids (NSSCs) as our audio fingerprints and preprocess the known commercials to build the database. For the second part, we apply a three-step process to search for any matches as the user requests, which comprises candidate search, decision-making and time verification. This process is performed for every N1 (N1=15 in our application) frames if the search result is negative. Once a match is confirmed, we skip the frames left in the commercial and use the frame after it to start a new process. Our experiment results are satisfactory based on the commercial and TV program data in our database. Moreover, it shows that our PC-based application is robust against degradation during real broadcast and recording.