After introducing myself and where I come from, in this talk I will focus on 3 projects I have been working in the last year. The first one is a novel pattern matching algorithm, based on the well known Dynamic Time Warping. The presented algorithm can be used to find real-valued subsequences within a longer sequence, without prior knowledge of their start-end points. I have applied the algorithm for the task of acoustic matching, for which I will show some preliminary results. Then I will continue to explain a second DTW-based algorithm, this one being able do an online of two musical pieces. One of the music pieces can be input life or be retrieved from an audio file, while the second one is extracted from an online music video. The online alignment allows for the music video to be played in total synchrony with the corresponding ambient/recorded audio. Finally, I will talk about video copy detection, which is the task of finding video duplicate segments within a big database. I will explain our multimodal approach, based on audio-visual change-based features.