# Constraint-Based Time-Scale Modification of Music Recordings for Noise Beautification
## 6 Experiments
As shown by Figure 6a, the reference APs were matched to source APs, while the periods of silence in the reference signal R-MRI-06 were filled without introducing local temporal distortions in the modified source signal. When listening to the superposition of the noise signal and the adaptive music signal, no major artifacts can be noticed in the music. A similar example is shown in Figure 6b. While the pulse trains of the noise signal R-MRI-24 are spaced again in a locally periodic fashion, the periods of silence between these pulse trains occur in a more irregular fashion. Still our approach is capable of mapping the eighth-note pulse grid of the music signal S-Fandango to superimpose the knocking sounds of the MRI signal without introducing too much local distortions in the music. Besides the temporal adjustment, the selection of suitable music pieces serving as source signals is also crucial in a noise beautification scenario. In particular, the selection may be based on a patient's personal taste or on perceptual criteria. For example, the Balkan rock music piece S-Fandango may be more suitable to blend with the knocking sounds produced by the MRI scanner than the piano piece by [PERSON]. When selecting a piece of music, aspects such as harmony or timbre are important cues to blend the noise and music signal [4; 7]. Also, higher-level temporal structures (e.g., the meter or regularly recurring patterns such as a rift) and boundaries between musical parts may be considered as additional constraints in the mapping  
Figure 5: Illustration of the interactive website for a toy example. process. Incorporating such cues into the music selection, mapping, and adaption processes constitutes interesting research directions. As a third illustrative example, Figure 6c shows a heartbeat signal with the typical \"lub-dub, lub-dub\" patterns used that define the references APs. When using our DP-based mapping approach, the sixteenth-note pulse grid of the source signal S-Bach is nicely mapped onto these patterns, where every third pulse of the music falls into a period of silence (between a \"dub\" and the subsequent \"lub\"). This way, all the \"lub-dub, lub-dub\" reference APs are superimposed, while the music signal has a nearly constant tempo. Even though generally leading to similar results, local outliers occur more often for the greedy approach compared to the DP-based one. This is also illustrated when listening to the superimposed signals provided on our websites. As a final example, we consider the synthetic noise signal R-Syn-In as reference signal, which consists of a click-track of increasing speed (starting with 78 BPM and ending with 450 BPM). Note that even though our mapping algorithms were designed to cope with locally periodic pulse tracks (as occurring in our MRI application), this non-periodic reference signal nicely illustrates the behavior of our approaches. The greedy strategy maps the source APs to the reference APs while trying to keep the overall musical pulse at a constant tempo. As a result, as illustrated by Figure 6d, the gaps (of decreasing size) between subsequent references APs are filled with a decreasing number of source APs. Using our DP-based strategy yields the solution as shown in Figure 6e. Here, the source APs are mapped to the reference APs also with increasing tempo, which minimizes the accumulated second order differences.