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All issues Volume 10 (2026) Acta Acust., 10 (2026) 55 Full HTML
Open Access
Issue
Acta Acust.
Volume 10, 2026
Article Number 55
Number of page(s) 13
Section Environmental Noise
DOI https://doi.org/10.1051/aacus/2026051
Published online 03 July 2026

© The Author(s), Published by EDP Sciences, 2026

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1 List of Abbreviations

BC: Bird chirping

CC: Cricket chirping

ES: Emotional Salience

IAMS: Informational-Attentional Masking Sounds

SNR: Signal-to-Noise Ratio

W0: Water stream 0

W1: Water stream 1

2 Introduction

In recent decades, restorative urban spaces have gained great attention among the communities of scholars, psychologists, landscape architects, city planners, engineers and policy makers [1, 2] due to their potential in promoting people’s wellbeing [3] through the physical [4] and psychological [5] restoration, as well as the social interaction [6]. The highest potential for improving citizens’ quality of life is represented by urban green spaces [7], where the presence of green, e.g., grass, plants or trees, and blue, e.g., fountains, ponds, and water, elements [8] fosters, across the age factor [9], the likelihood of feeling away from the stressful urban context and, at the same time, fascinated by the richness and harmony of the park elements [10] in completely agreement with the principles of the Stress Recovery Theory of Ulrich [11] and of the Attention Restoration Theory of Kaplan [12]. Depending on their extension and characteristics, urban green spaces can contribute to providing further beneficial effects, both for individuals and the environment. It can help to mitigate local microclimate [13] and air pollution [14], improving also the soundscape quality [15]. Large green areas are, however, not easily accessible by the public as, in most cases, their distance is well beyond the buffer distance of 300 m recommended by the World Health Organisation [16], or within a 500 m radius of home indicated by de Roo in [17]. For instance, in their study on the cities of Rouen, Brussels and Luxembourg, Schindler et al. [18] revealed that residents travel almost 2 km to reach their urban green spaces of at least 0.5 ha.

Latter observations have stimulated researchers to investigate alternative and smaller spaces inside the urban fabric able to provide high accessibility and restorative potential for the local communities. Masullo et al. [19] have highlighted correlations between the soundscape, appreciation, maintenance/management and importance/relevance of 10 cloisters and courts, or khans, of the historical centres of Naples (Italy) and Istanbul (Turkey) and the visitors restorativeness. Narandžić and Ljubojević [20] proposed small-scale interventions to revitalise six types of urban pockets: courtyard-, road nearby-, framed/island-, passage-, under-bridge- and within city blocks-pockets. Zhai et al. [21] studied the restorative effects of different site types, i.e., lawn, water, and plaza, and spatial scales of small urban open spaces, suggesting that more restoration benefits can be realised through more small urban open spaces built with lawn and water. Peschardt et al. [22] investigated the primary role of small public urban green spaces in dense city areas for socialising, and rest and restitution. Focusing on pocket urban parks, they have intrinsic characteristics that may contribute to lowering restoration ratings, such as: a general lack of vegetation and the disturbance from the surroundings, due to the road traffic, a poor shielding from the surroundings and the use of hard surfaces [23]. Consequently, pocket urban parks can be directly exposed to moderate-to-high road traffic noise levels (60–80 dBA) [24], reducing significantly their frequency of use and appreciation. As emerged through the original (long-term) version of the Harmonica Index [25] and its applications [26–28], the equilibrium between the background noise and noise events is strictly related to the personal noise annoyance experienced in these spaces. Furthermore, by developing a modified version of the index for short-term intervals, Masullo et al. [29] highlighted that, while the background of road traffic noise level is always positively correlated with noise annoyance (high sound pressure levels correspond to high noise annoyance), the events highly depend on their quality (positive events reduce noise annoyance, and viceversa). The role of sound in small urban restorative spaces has been previously investigated by several researchers, with and without considering the moderator effect due to visual stimuli [30–43]. Nordh et al. [30] investigated on how different combinations of natural sounds and anthropogenic noise in urban green spaces may influence the restorative potential of small urban parks. They showed that park soundscapes with a rich array of perceived bird sounds and minimal perceived traffic noise offer the greatest perceived restoration. The research on the beneficial effects of the introduction of continuous virtual or real natural sounds, such as water and bird sounds, has been largely expanded during the last two decades [31]. Research has demonstrated that the presence of water sound can significantly improve the conscious people’s restoration [32, 33], noise annoyance [34], as well as enhance their mental state [35]. By two listening experiments, repeated in a laboratory [36] and in situ [37], where participants’ electroencephalography signals were measured during a controlled noise exposure, Li et al. have demonstrated that the introduction of dynamic augmented sounds, short-duration sequences of a water stream sound in that case, affected participants’ mental state, improving their relaxation. However, these beneficial effects also depend on the balance between characteristics of water sounds and road traffic noise [38]. While high flow-rate fountains, which generate steady-state sounds, result inherently as unpleasant [39, 40] and should not be used for these scopes, on the contrary, gentle water streams [41] result in very efficient. Regarding the playback volume for continuous water sounds, it should be set to or not less than 3 dB below the road traffic sound level [42, 43].

As emerged by the large survey, over 1000 interviews over four seasons, by Yang and Kang [44] in Sheffield, bird sounds together with water sounds, are among the most preferred, including more than 75% of the interviewed, and least annoying sounds too, with less than 10% of the people, in urban contexts. Moreover, bird sounds may encourage positive affective appraisals of the soundscape and induce a reduced arousal in the individuals, by fostering their restoration from stress or fatigue [45–47] through the activation of the effortless attentional and the connection with nature. However, not all bird sounds are perceived as pleasant. Cox and Gaston, in line with a previous survey in U.K. [48], recognised robins as the most favourite birds [49]. Moreover, Ratcliffe et al. [50] distinguished between bird sounds with high, i.e., greenfinch, blackbird, robin, house sparrow, goldfinch, chaffinch, moderate, i.e., starling, feral pigeon, carrion crow, goldfinch, collared dove, and low, i.e., Silver Gull, Kookaburra, Red Wattlebird, Magpie, perceived restorative potential. Bird sounds which were judged to be highly restorative generated affective appraisals of positive valence and low arousal. While there is evidence that, in urban parks, road traffic noise reduces the potential benefits of bird sounds [51, 52], viceversa, even more studies promoted experiences of bird sounds in urban parks [53], or investigated their contribution on road traffic noise mitigation [54]. Minor attention was, instead, paid to the effects of other natural sounds, such as those emitted by insects. Among them, the most interesting is the potential benefit of cricket chirping [55, 56], which was found to be pleasant for the human mind by Satoshi et al. [57].

With the scope of mitigating the negative effects of urban noise, researchers have largely investigated the possibility of using the above-mentioned natural sounds as partial or attentional markers. Wu et al. [58] employed sound masking by mixing sounds extracted from five masker sound datasets to abate construction noise. Schulte-Fortkamp [59] remodelled the soundscape of the Nauener Platz park in Berlin (Germany), designing “audio islands”, where integrated speakers played continuously preset sounds, such as bird sounds and shingle beach shore sounds, to improve the citizens’ experience. Steele et al. [60] investigated the effect of the use of Musikiosks. Results showed that, although people did not change their ratings of calmness, appropriateness, and restoration, they reduced their mention of traffic noise. Playback music in open public spaces was found to statistically affect the duration of stay for people stopping in the area [61]. The selection of the most appropriate masker sounds and of their gain levels is critical, as it depends on many factors. Van Rentenghem et al. [62] explored these aspects in a real-world soundscape augmentation setting, in a traffic-exposed park. Their results indicate that people like a balanced combination of various types of natural sounds, and that they tend to maximise the signal-to-noise ratio (SNR) relative to the background noise, mainly in the frequency range between 2.5 kHz and 8 kHz. While introducing pleasant background sounds mitigates the negative effects of road traffic noise, on the other hand, when road traffic is scarce or absent, it inevitably causes an increase in the existing sound levels, preventing visitors from benefiting from very quiet periods. This led researchers to propose and investigate various types of automatically-activated audio augmented systems. Xu et al. [63] have demonstrated that loudness and spectral centroid of music are significantly correlated with annoyance reduction percentage when the music is used to mask the low-frequency noise produced by near road traffic. Van Renterghem et al. [62] asked the users of an urban park in Ghent, largely exposed to road traffic noise, to combine eight types of natural sounds, including insect/bird sounds, water sounds and meteorologically induced sounds, played back by a hidden loudspeaker, until they personally felt the soundscape optimised. Furthermore, in a park bordering a highway in the city of Antwerp (Belgium), they present an in-situ multi-step procedure to co-creative water feature sound augmentation by balancing sound pleasantness and traffic audibility well [64]. Using birdsong (sparrow) and a water sound (stream) in a laboratory study, Hong et al. [65] found that SNR and temporal features were key soundscape design factors. A further in-situ experiment in Singapore, with the same audio stimuli [66], highlighted that overall preferred levels of birdsong were 5 dB higher than water sound. Cobianchi et al. in [67] stated that the unpredictable short-timescale variation of the urban acoustic environment (vehicles’ passing or the odd moments of quietness due to the cessation of roadworks) makes any given pre-determined static soundscape a non-optimal implementation of soundscape re-design.

Only a few papers have investigated the impact of making the playback ambient responsive and adaptive to the environment through an algorithmic approach. Among the first dynamic applications, Licitra et al. [68] proposed the use of an artificial soundscape generation system capable of choosing the proper multi-channel soundtracks from a music database of meta-compositions and processing them in real time to match the features of the noise to be masked. In Brighton and Hove, Lavia et al. [69] used a hybrid approach, the playback material was programmed in order to match the type of maskers and sound levels to specific pre-determined time periods, according to known changes in the local acoustic environment. In [70], the playback material was curated in real-time through human intervention. More recently, some authors used automatic activations to generate positive sounds. Watcharasupat et al. [71] utilised a deep learning model to perform joint selection of the optimal masker and its gain level for a given soundscape. More recently, Lam et al. [72] tested the introduction of an automatic masker selection system utilising natural sounds to mask or augment traffic soundscapes, employing artificial intelligence in adapting changes over time in the ambient environment to maximise “ISO-Pleasantness”.

Although most state-of-the-art studies have used long-duration sounds, short-duration sounds are emerging as a less intrusive solution, as they can provide more specific masking interventions focused on the negative events of the road traffic noise, preserving at the same time the existing quietness between vehicles’ passing by. Moreover, in relation to the introduction of these automatic masker systems and to the perceptual response of individuals, some challenges still remain uninvestigated. Therefore, in this paper, the perceptual responses of individuals virtually sitting in a pocket urban park and exposed to the external road traffic noise, in different simulated scenarios: without and with the automatic activation of short informational-attentional masking sounds (IAMS) consisting of water, birds and cricket cues, at different SNRs have been investigated and compared.

Note that, as the paper focuses exclusively on the possibility of using short IAMS instead of continuous masking sounds by testing a new methodology for their activation, the contribution of the visual domain in moderating the auditory perception has been deliberately neglected. The aim is to answer the following two sets of research questions (RQ) and investigate the research hypotheses (H1 and H2) (Tab. 1). The corresponding null hypotheses (H0) were used for the statistical analyses.

Table 1.

Research questions and research hypotheses.

3 Material and methods

A within-experimental design was prepared to investigate the study hypotheses. The participants were engaged in a laboratory listening experiment. Each of them experienced different acoustic environments presented in random order by combining an existing condition with only the presence of road traffic noise and the activation of short IAMS cues reproducing, separately, different natural cues at different SNR. During the listening, participants completed the ISO 12913-2 [73] and Emotional Salience [74] questionnaires, and evaluated the Noise Annoyance [75] of the experienced scenario. Statistical analyses were conducted to assess the effect of using automatic audio augmentation with informational-attentional masking cues on the perceptual and emotional responses of individuals.

3.1 Experimental design

Starting from the same road traffic background noise condition, which represented the control condition of the experiment (CTRL), a full factorial experimental design used four different IAMS cues reproducing, separately, two different water streams and two different chirpings, particularly birds and crickets, at four different SNR, at −3, −6, −9 and −12 dB to the background noise, was considered. A total of 17 experimental conditions, 1 CTRL  +  (4 IAMS  ×  4 SNR), were prepared and evaluated by each participant involved in the experiment.

3.2 Audio material: road traffic noise and natural sound cues

Road traffic noise binaural recordings were carried out at approximately the same distance, about 10 m from the centre of the closest lane, and with the same head orientation, orthogonal to the road flow, in two pocket urban parks facing the same local two-way street (Fig. 1) of the municipality of Pozzuoli (Naples, Italy).

Thumbnail: Figure 1. Refer to the following caption and surrounding text. Figure 1.

Two pocket urban parks A and B. Listener point of view (top) and overview (bottom).

From previous recordings, five vehicles’ pass-by excerpts of representative different vehicle typologies, i.e., motos, scooters, cars, small trucks, and passing by directions, e.g., left to right and viceversa, were extracted and mixed with a recording representing a lower and continuous road traffic noise in the same context. The 1 minute mixed-down binaural soundtrack, see different spectrograms in Figure 2, was used as a control scenario and to generate the augmented acoustic environment, as described below. Four different types of 2 s informational-attentional masking sound cues were used to augment the existing CTRL scenario. The sound cues were representative of having different spectro-temporal properties. The two different water stream soundtracks, denoted as W0 and W1, were recorded in a rural area by using a Zoom H6 Hand-Recorder device equipped with Rode NTG-2 microphone. The two chirping soundtracks, a cricket and a bird (robin) chirping, denoted respectively as CC and BC, were downloaded from the sound database Freesound [76]. Each of sound cues were convolved with the frontal head-related transfer function (CIPIC Database, KEMAR large pinna) [77].

Thumbnail: Figure 2. Refer to the following caption and surrounding text. Figure 2.

Spectrograms of the CTRL and augmented scenarios at SNR −3 dB: (a) CTRL, (b) W0, (c) W1; (d) CC and (e) BC.

From each of the four original soundtracks, five different 2 s sound cues, see the spectrograms in Figure 3, were extracted and included in specific folders, which were furthermore played back. The latter decision was intended to avoid boring the participants by activating the same sound cue, providing a more natural augmented environment. Both the selection of the sound cues from the specific folder, as well as the order of the masking conditions, were randomly and automatically activated during the playback of the control scenario through MATLAB. To limit the number of automatic IAMS activations, two activation thresholds were set: the current short (1 s) sound equivalent level and the slope (in dB/s) of the road traffic noise. After preliminary evaluations regarding the frequency of automatic activation of the IAMS, the threshold values to be satisfied were set to 45 dBA for the current short Leq and to 2 dB/s for the rapidity of the variation of the short Leq.

Thumbnail: Figure 3. Refer to the following caption and surrounding text. Figure 3.

Spectrograms of five samples per each IAMS category: W0, W1, CC and BC.

3.3 Questionnaires

The main questionnaires were preceded by preliminary questions about general information: age, gender, residential area, education level and occupation category, level of frequentation of refuge pokets (Tab. 2). Two questionnaires were used to investigate the perceptual and emotional outcomes of introducing augmented sounds into an existing soundscape of a small urban park affected by road traffic noise. The first questionnaire consists of the 8-item questionnaire (Tab. 3) based on ISO/TS 12913-2:2018 [73], while the second (Tab. 4) consists of 12 items that span the perceptual (6 items) and emotional (6 items) dimensions of Emotional Salience [74]. The translations of the question items in the Italian language were carried out in line with the Soundscape Attributes Translation Project (SATP) [78]. Two additional (verbal and numeric) questions concerning noise annoyance based on ISO/TS 15666 [74] were also included (Tab. 5).

Table 2.

Preliminary questions.

Table 3.

ISO/TS 12913-2.

Table 4.

Emotional Salience questionnaire.

Table 5.

ISO/TS 15666 questions.

4 Laboratory experiment

4.1 Laboratory setup

The listening test was carried out in the test room of Sens i-Lab, see Figure 4, the key laboratory of the Department of Architecture and Industrial Design of the Universitá degli Studi della Campania “Luigi Vanvitelli”. The audio stimuli were played back by an HP Envi Laptop connected to a Binaural Playback Unit (Head Acoustics, Herzogenrath, Germany) and HD closed headphones, DT700 ProX. The sound levels of the headphones were calibrated using an artificialhead HSU III.2 coupled with a 4-channel system SQobold (Head Acoustics, Herzogenrath, Germany) and reproducing a sound equivalent level of 60 dBA (66 dB) under the control condition.

Thumbnail: Figure 4. Refer to the following caption and surrounding text. Figure 4.

Experimental session in the Sens i-Lab.

4.2 Participants

Thirty subjects, fourteen males and sixteen females, participated in the listening test. Most of them (80%) were students or researchers of the Department of Architecture and Industrial Design. The age range was 18–45 (18–25, the 57%; 26–35, the 30%; 36–45 the 13%). Most of them live in urbanised areas (30% in an intermediate urbanised area, 40% in suburbs and 20% in a city centre), only 7% in rural areas. They seek refuge in spaces away from traffic, “rarely” for the 33%, “sometimes” for the 40% and “often” for the 23%. The elements they first look at are those green (Mean = 4.7) and for physical relaxation (Mean = 4.4), then the water ones (Mean = 4.0) and for socialising (Mean = 4.0). They primarily search a sound environment with “no road traffic noise” (Mean = 4.2) and “no children’s screams” (Mean = 3.6), while they want the presence of “natural sounds” (Mean = 4.5) and “water sounds” (Mean = 3.9). Less important are the “silence” (Mean = 2.8) and the presence of “music” (Mean = 2.9). Finally, none of them reported having had hearing impairments in their life.

4.3 Procedure

The experiment was conducted in accordance with the Declaration of Helsinki. The methodology used in this study, shown in Figure 5, was approved by the Ethical Committee of the Department of Architecture and Industrial Design of the Universitá degli Studi della Campania “Luigi Vanvitelli” (CERS).

Thumbnail: Figure 5. Refer to the following caption and surrounding text. Figure 5.

Scheme of the experiment procedure.

All participants signed an informed consent form before participating in the test and were informed of data privacy and their use in this research. Once in the test room, in the presence of an operator, participants read the instructions to contextualise the listening experience and conduct the test: “Dear participant, below you will be presented with several sound scenarios representing those of a pocket urban park located near a road with some vehicles passing by. Imagine yourself in one of these pocket parks in our cities and listen carefully to the sound scenarios presented to you. For each sound scenario, you will be asked to provide us with your feedback on the questions asked in the questionnaires below…” started answering the preliminary questions described above, then wore a pair of headphones and started listening to the auditory scenarios. In order to have as much as possible real-time feedback on their experience, they were instructed to start answering the above-mentioned questionnaires just after the complete pass-by of the first vehicle. This allowed participants to complete the answering bundle just a few seconds after the end of each listening.

4.4 Statistical analyses

After the ground-truth label of ISO Pleasantness/Eventfulness [73] and Positive and Negative Emotional Salience [74] were calculated for each auditory scenario, the following statistical analyses were carried out:

  • (RQ1.x) One-Way RM-ANOVAs, including the control condition, were conducted on ISO Pleasantness and Eventfulness, and on the Positive and Negative dimensions of Emotional Salience. Further non-parametric Friedman tests were also carried out on the 5- and 11-item Noise Annoyance questionnaires.

  • (RQ2.x) Two-Way follow-up RM-ANOVAs that neglect CTRL condition and that treated IAMS and SNR as four levels factors, were conducted on the ISO Pleasantness and Eventfulness, on the Positive, Negative and Total (ESTOT = ESPOS − ESNEG) dimensions of Emotional Salience, as well as on the 11-item Noise Annoyance questionnaires. Further One-Way ANOVAs were also performed on the 5- and 11-item Noise Annoyance questionnaires, grouping the ratings per IAMS and SNR.

The level of significance was set at α = 0.05 for all statistical analyses, and no data transformations were applied. While One-Way repeated-measures ANOVAs were followed by Dunnett’s post-hoc tests to compare each experimental condition against the control (CTRL), a test specifically designed for multiple comparisons with a single reference group, in the Two-Way follow-up ANOVAs, a Bonferroni correction was applied. Bonferroni correction was appropriate because the analyses involved multiple pairwise comparisons, providing a conservative control of the family-wise error rate, reducing the likelihood of Type I errors across all comparisons.

5 Results

This section shows main results of this work. Firstly, the main effect obtained by the introduction of short IAMS on both the ISO 12 913 dimensions, on the positive and negative dimensions of the Emotional salience, and on the perceived noise annoyance are presented. Then, results obtained on the same dependent variables, due to the use of different IAMS types and SNR levels are described.

5.1 Effectiveness of audio augmented scenarios

Regarding the potential improvement of the soundscape (RQ1.1), the One-Way RM-ANOVA in the ISO pleasant dimension shows that the activation of IAMS provides significant improvements, F(6.14, 171.95)=4.3177, p <  0.001. In particular, Dunnett’s post-hoc test shows that, with respect to the existing control scenario, this occurs for all IAMS types and SNR conditions (Fig. 6). No significant results emerged for the ISO eventful dimension.

Thumbnail: Figure 6. Refer to the following caption and surrounding text. Figure 6.

Mean values and standard errors of ISO pleasantness and pair comparisons.

Representing the two dimensions on the ISO pleasant – ISO eventful plan, it is possible to observe how the soundscape perception area in the control condition has a horizontal shift toward a more positive pleasant dimension in all conditions (Fig. 7).

Thumbnail: Figure 7. Refer to the following caption and surrounding text. Figure 7.

ISO pleasant – ISO eventful graph. Comparison between the CTRL and the different IAMS conditions.

Concerning the potential improvement of Emotional Salience (RQ1.2), One-Way RM-ANOVAs on the Positive (ESPOS) and Negative (ESNEG) dimensions show that, for the Positive dimension, IAMS activation significantly improves positive perception, F(6.29, 169.80)=3.41, p = 0.003. In particular, Dunnett’s post-hoc test shows that, with respect to the existing control scenario, this occurs for almost all IAMS types and SNR, except for the conditions with the crickets chirping (Fig. 8). On the contrary, for Negative dimension of Emotional Salience, results show that the activation of IAMS significantly reduces negative perception, F(7.05, 197.45)=3.64, p <  0.001. In particular, Dunnett’s post-hoc test shows that, with respect to the existing control scenario, this occurs for all IAMS types and SNR conditions (Fig. 9). Regarding the potential reduction of noise annoyance (RQ1.3), the non-parametric Friedman test repeated on the 11-(ANN-11) and 5-(ANN-5) items Noise Annoyance questionnaire showed that ratings in the presence of IAMS significantly reduce the perceived noise annoyance of the car pass-by, respectively, X(16)=28.09, p = 0.031 (Fig. 10) and X(16)=29.27, p = 0.022.

Thumbnail: Figure 8. Refer to the following caption and surrounding text. Figure 8.

Mean values and standard errors of ESPOS and pair comparisons.

Thumbnail: Figure 9. Refer to the following caption and surrounding text. Figure 9.

Mean values and standard errors of ESNEG and pair comparisons.

Thumbnail: Figure 10. Refer to the following caption and surrounding text. Figure 10.

Mean values of ANN-11.

5.2 Effect of IAMS types and/or SNR levels

The follow-up Two-Way RM-ANOVAs on ISOpleasant and ISOeventful dimensions show no significant main effects of IAMS types and SNR levels, as well as no interactions (RQ2.1). Similarly, also for the −5 and −11 Noise Annoyance, the RM-ANOVAs show no significant main effects of IAMS types, SNR levels, and interactions (RQ2.3).

Regarding the Positive and Negative dimensions of Emotional Salience, the Two-Way RM-ANOVAs still show not significant main effects of IAMS types, SNR levels, and interactions. However, a tendential significant main effect, F(1.76, 47.56)=3.306, p = 0.051, emerges only combining two ES ratings, in a single total index, ESTOT = ESPOS − ESNEG. Bonferroni post-hoc test shows that in the case of CC IAMS, ESTOT is reduced than W0, W1 and BC IAMS (Fig. 11).

Thumbnail: Figure 11. Refer to the following caption and surrounding text. Figure 11.

Mean values and standard errors of ESTOT.

6 Discussion

This study assessed and compared the perceptual and emotional responses of individuals who were virtually situated in a small, restorative urban pocket while exposed to external road traffic noise, in different conditions, without and with the introduction of short sounds activated by an automatic system for audio augmentation. In line with previous studies [29], the possibility of using positive sound events, informational-attentional masking sounds (IAMS), to detach listeners’ attention from the prominent negative sound events of road traffic, such as vehicles or motorcycles passing by, was explored. To this aim, different characteristics of audio augmentation were combined: (1) a short sampling time (1 s) to verify the activation conditions of IAMS; (2) the contemporary satisfaction of two different activation conditions, a minimum background noise and a minimum positive slope of the Leq, A trend, and (3) the activation of IAMS with short-duration (2 s).

The above-mentioned characteristics, in line with Cobianchi et al. [67], have the following advantages:

  • A short sampling time and a continuous control of the evolution of the short-term A-weighted sound equivalent levels respond to the need to provide a rapid and specific mitigating intervention of the noisiest negative events generated close to the listening position in the urban pocket.

  • An activation based on the double check, on the overcoming of a background sound level threshold and of a minimum slope to detect the approaching increase of sound level, together with a short duration of the IAMS, allows for avoiding generating a synthetic scenario, where the augmented sounds are played back too frequently or for a prolonged time. This allow to keep quiet, as much as possible, during the time intervals between vehicles’ pass-by.

This approach produces only a minimum alteration of the sound experience under pass-by noise. This is substantially new both, with respect to the more traditional based on a fixed SNR [64] and from the most advanced cloud-based Automatic Masker Selection System (AMSS) of Lam et al. [72] which analyse the 30 s road traffic noise to automatically select the masker-gain and to choose the combination of continuous (more than 2 min) natural sounds to maximise the ISO pleasantness.

Results have shown that, rather than continuous playback of masking sounds the activation of short IAMS of 2 s represents a valid strategy to improve the existing urban pockets threatened by the road traffic noise. More in detail, water sounds and chirping demonstrated to significantly improve the pleasantness dimension (ISO pleasant), while not the eventfulness (ISO eventful) of the site. This means that short IAMS activated according to specific thresholds seems to act on the valence dimension of the site without altering or conflicting with the temporal evolution of the event in the site, which remained unchanged. On the other side, regarding the emotional sphere, emotional salience ratings showed that water and bird sound foster positive judgement of the site’s experience, reducing, contemporarily, the rating of negative emotions. However, this is not completely true for crickets, which, even though they reduce negative judgment, are unable to enhance the positive value of the experience.

Our results highlight that the use of short IAMS seems to be less sensitive to the setting of SNR. In fact, despite keeping the SNR fixed, as a consequence of following the variability of the road traffic noise level, the gain (and sound level) of the IAMS changes accordingly, making the distinction among the different SNR settings less clear. This aligns with the results of Hong et al. [65], which found a general reduction of the preferred SNR of the same birdsong and water sounds passing from a traffic noise level of 65 to 75 dB. From a technological and applicative point of view, the results of this study substantiate what emerged in [78], indicating that the development of adaptive soundscaping systems combining databases of short and different [30] natural sounds, more or less complex algorithms for the activation of audio augmentation, as well as appropriately positioned loudspeakers can enable an improvement of staying in small restorative urban pocket through a passive, real-time, and user-centred approach.

7 Limitations

Despite very promising research findings, some limits due to the experimental setting do not allow for generalising the results. The most important refer, inevitably, to the limited IAMS typologies were used in the experiment, as well as the preliminary setting of the activation thresholds. The first aspect should be faced by generating a database of short IAMS to use for the extraction of maskers’ sound cues, i.e., per single category or mixed (more categories), while the second by optimising the activation thresholds according to a maximum number of activations, the existing type of road traffic noise and the background noise of the context. This should also be done considering contextualisation issues of the selected IAMS typologies, i.e., by testing if the use of uncommon/common typologies of sound cues at a site, or in a specific part of the day (e.g., morning, sunset), can play a significant role in the individual’s experience of the site.

Another important aspect is to extend the research to different typologies and volumes of road traffic to verify if the set thresholds still lead to similar results and to investigate on the strategies (e.g., AI sound source recognition) to avoid potential unwanted activations. A further important aspect concerns the ecological validity of the results which need the gradual integration and modification of the several variable existing in a real site. In particular, future investigations on the IAMS use should extend what emerged in this experiment, investigating the moderator effect of visual elements/scenarios: by introducing controlled visual stimuli, by videowalls or immersive VR lab settings, or by organising in situ experiments, giving up control of some sensory stimuli in favour of real-life situations.

8 Conclusions

Consistent with the recent literature, this research showed that the augmented-audio systems based on short IAMS and automatically activated can represent a valid and non-invasive noise-mitigating strategy for urban pockets. The typologies of tested IAMS, water and chirping, have had almost the same effects within all the SNR range −3 to −12 dB, except for the crickets which is effective in improving only negative rating. Their effect is dual: reduces the perceived noise annoyance and improve the perceptual and emotional experience of individuals exposed to road traffic noise. Their application includes all cases where road traffic noise induces unwanted arousal and negative perception [78], as in the case of people who stop in small restorative urban green pockets. Advances in this topic will help to design and optimise the characteristics of future audio-augmented systems, which are expected to find even more applications in urban contexts [79] as soundscapes interventions [80].

Conicts of interest

The authors declare no conflict of interest.

Data availability statement

Data are available on request from the authors.

Ethics approval

The research protocol (2025-CERS05) was approved by the Ethical Committee of the Department of Architecture and Industrial Design of the Universitá degli Studi della Campania “Luigi Vanvitelli”.

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Cite this article as: Masullo M. & Navarro J.M. 2026. Introducing short informational-attentional masking sounds to improve staying in pocket urban parks: a laboratory study. Acta Acustica, 10, 55. https://doi.org/10.1051/aacus/2026051.

All Tables

Table 1.

Research questions and research hypotheses.

In the text
Table 2.

Preliminary questions.

In the text
Table 3.

ISO/TS 12913-2.

In the text
Table 4.

Emotional Salience questionnaire.

In the text
Table 5.

ISO/TS 15666 questions.

In the text

All Figures

Thumbnail: Figure 1. Refer to the following caption and surrounding text. Figure 1.

Two pocket urban parks A and B. Listener point of view (top) and overview (bottom).
In the text
Thumbnail: Figure 2. Refer to the following caption and surrounding text. Figure 2.

Spectrograms of the CTRL and augmented scenarios at SNR −3 dB: (a) CTRL, (b) W0, (c) W1; (d) CC and (e) BC.
In the text
Thumbnail: Figure 3. Refer to the following caption and surrounding text. Figure 3.

Spectrograms of five samples per each IAMS category: W0, W1, CC and BC.
In the text
Thumbnail: Figure 4. Refer to the following caption and surrounding text. Figure 4.

Experimental session in the Sens i-Lab.
In the text
Thumbnail: Figure 5. Refer to the following caption and surrounding text. Figure 5.

Scheme of the experiment procedure.
In the text
Thumbnail: Figure 6. Refer to the following caption and surrounding text. Figure 6.

Mean values and standard errors of ISO pleasantness and pair comparisons.
In the text
Thumbnail: Figure 7. Refer to the following caption and surrounding text. Figure 7.

ISO pleasant – ISO eventful graph. Comparison between the CTRL and the different IAMS conditions.
In the text
Thumbnail: Figure 8. Refer to the following caption and surrounding text. Figure 8.

Mean values and standard errors of ESPOS and pair comparisons.
In the text
Thumbnail: Figure 9. Refer to the following caption and surrounding text. Figure 9.

Mean values and standard errors of ESNEG and pair comparisons.
In the text
Thumbnail: Figure 10. Refer to the following caption and surrounding text. Figure 10.

Mean values of ANN-11.
In the text
Thumbnail: Figure 11. Refer to the following caption and surrounding text. Figure 11.

Mean values and standard errors of ESTOT.
In the text

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