## 1 Introduction
Although traffic noise is indeed the most common type of noise, through several conducted studies [29; 30] there are noise sources which have arisen with a higher level of annoyance when compared to traffic noise. In that sense this paper aimed to investigate these sound sources with the core objective of determining the acoustic parameters which could unambiguously describe them. From the acoustic point of view, there are several studies which show that it is possible to calculate an \"annoyance level\" of a certain sound or an acoustic environment [31; 32] taking into account the objective acoustic parameters such as loudness, sharpness and roughness [33; 34; 35; 36; 37]. Moreover, another part of acoustic environment research deals with their distraction properties and how characteristic sounds influence people performing logical, mathematical and other concentration-demanding tasks [38; 39]. In our previous research we proposed a simple acoustical model, which allows one to quantify how much some kind of typical urban acoustic environment is subjectively perceived in terms of affecting the listeners' concentration [31]. For that purpose, we recorded several different acoustic environments which were then reproduced to the listeners. It was found that the linear model is adequate for calculating the parameter that we termed as the total distraction coefficient (\(TDC\)) [31]. The total distraction coefficient (\(TDC\)) is a numerical value of a certain acoustic environment and can serve as an objective parameter for the evaluation of different acoustic environments. It is defined by the following expression:  
\[TDC=0.1\cdot L_{DIF}+0.02\cdot LGD_{DIF}+0.44\cdot S_{DIF}, \tag{1}\]  
where \(L_{DIF}\), \(LGD_{DIF}\) and \(S_{DIF}\) are defined as a ratio of difference values and the average value of the three considered objective parameters themselves (loudness, loudness growth difference and sharpness). For instance, the lowest \(TDC\) was obtained for the acoustic environment of stream. Namely, we have also found in [40] that it is the sudden and unexpected signals of short duration that are perceived as most distracting and annoying, hence we decided to put some more focus on them in order to determine which parameter of such signals makes the key influence on the _TDC_. To extend this research in this paper we present an additional study involving short distracting signals. Short signals such as children's streams, a car passing by and the sound of a grinder which were used in this study (see Figure 1) were chosen due to the fact that in our previous research [31; 40] these signals were characterized by participants as extremely annoying and distracting, i.e., they influenced the quality of life in a negative way. In addition, these signals are quite common for each resident living in a typical urban environment (i.e., usually near every apartment building there is a park, a road and some type of store). In [37; 41] the studies established that loudness, duration and loudness growth rate have an impact on the overall human perception of an acoustic environment, however we actually desire to investigate, focus and prove how significant and major that impact is in terms of human annoyance. Considering our previous research, the null hypothesis of this study was that the mentioned parameters will be ranked by the study participants in the following way: loudness, duration and in last place the loudness growth rate. We expected that the higher levels of loudness would have a more significant  
Figure 1: Short signals characterized by participants as distracting (based on [39]). impact on the annoyance than the duration of some typical sound signal. In addition, we wanted to determine when certain signals became annoying in terms of all three parameters.