@misc{vonBergVersuemerSteffensetal.2025, author = {von Berg, Markus and Vers{\"u}mer, Siegbert and Steffens, Jochen and Bitta, Joshua}, title = {Reproduction levels of outdoor soundscapes in the lab after in-situ exposure: participant responses and recording level envelopes}, publisher = {Zenodo}, doi = {10.5281/zenodo.17663267}, year = {2025}, abstract = {Supplemental material for https://doi.org/10.1051/aacus/2025062 To investigate loudness biases in the lab, where outdoor sounds are perceived as being too loud if reproduced with physically accurate levels in the lab, a listening experiment was conducted, where thirty-one participants visited a street and listened to the environmental sounds for one minute. These sounds were also recorded using a dummy head. Afterwards, participants listened to the recording in a quiet laboratory and adjusted its level as they remembered it. About half of the sample did this immediately, the other half about 20 min after the recording, during which the performed another listening tests. Afterwards, previous experience with acoustics, musical sophistication and noise sensitivity were assessed. The results revealed a mean gain adjustment of 8.9 dB below the original. The data uploaded here comprises participants gain adjustment, the recording levels averaged other A) the entire recording and B) the first and last 7.5s or 15s, respecitvely and all questionnaire responses as well as aggregate scores for musical sophistication and noise sensitivity, as well as a binary categorization of the respondent into laymen and experienced, based on their previous experience with acoustics. For sociodemographic information, participants age, sex and educational degree are reported as well. Content - 00_Description: - Description of the data files - Includes a list of explanation of the columns names in "data_questionnaires_aggregateLevels.csv - data_questionnaires_aggregateLevels.csv - Participants' adjusted recordings levels - Several level and loudness aggregates of each participant's recording that were analyzed in the paper - Participants' responses to the administered questionnaires - level_envelopes.zip - Archive with 31 CSV files containing level envelopes of each participant's recording. - A-weighted and unweighted level envelope for the dummy head's left and right ear - One-minute recordings with a temporal resolution of 125ms}, subject = {Psychoakustik}, language = {en} } @article{vonBergVersuemerBittaetal.2025, author = {von Berg, Markus and Vers{\"u}mer, Siegbert and Bitta, Joshua and Steffens, Jochen}, title = {Reduced reproduction levels of outdoor soundscapes are deemed appropriate - even after real-world exposure}, series = {Acta Acustica}, journal = {Acta Acustica}, publisher = {EDP Sciences}, issn = {2681-4617}, doi = {10.1051/aacus/2025062}, pages = {16}, year = {2025}, abstract = {Laboratory experiments in psychoacoustical and soundscape research indicate that participants perceive a reproduction sound level lowered by 8-10 dB as more plausible than the original level. This bias supposedly roots in an adaptation of perceptual loudness scaling to the laboratory environment, that is overall quieter than urban outdoor soundscapes. To gain further insights into the nature of such loudness bias, we conducted a listening experiment in both field and laboratory using a within-subjects design. Thirty-one participants visited a street and listened to the environmental sounds for one minute, while these sounds were also recorded using a dummy head. Thereafter, they listened to the recording in a quiet laboratory nearby and adjusted its level as they remembered it. About half of the sample did this immediately, the other half about 20 minutes after the recording. Results confirm a bias towards lower levels with a mean of about 8.9 dB, regardless of the time between the recording and the reproduction in the laboratory. Also, participants with higher musical abilities tended to select higher, more accurate levels, whereas noise-sensitive participants deemed lower levels appropriate. Results suggest that the hypothesized adaptation of perceptual scaling to the laboratory happens immediately and is affected by individual factors.}, subject = {Psychoakustik}, language = {en} } @inproceedings{vonBergBittaVersuemeretal.2025, author = {von Berg, Markus and Bitta, Joshua and Vers{\"u}mer, Siegbert and Steffens, Jochen}, title = {Investigation of auditory memory through loudness reproduction in the laboratory [Abstract]}, series = {DAS|DAGA 2025: 51st Annual Meeting on Acoustics, March 17-20, 2025, Copenhagen}, booktitle = {DAS|DAGA 2025: 51st Annual Meeting on Acoustics, March 17-20, 2025, Copenhagen}, publisher = {Deutsche Gesellschaft f{\"u}r Akustik e.V.}, address = {Berlin}, year = {2025}, subject = {Ged{\"a}chtnis}, language = {de} } @inproceedings{BlaettermannVersuemerSteffens2025, author = {Bl{\"a}ttermann, Patrick and Vers{\"u}mer, Siegbert and Steffens, Jochen}, title = {Loadings of Acoustical Metrics on Soundscape Items and their relation to Soundscape Dimensions across different datasets [Abstract]}, series = {DAS|DAGA 2025: 51st Annual Meeting on Acoustics, March 17-20, 2025, Copenhagen}, booktitle = {DAS|DAGA 2025: 51st Annual Meeting on Acoustics, March 17-20, 2025, Copenhagen}, publisher = {Deutsche Gesellschaft f{\"u}r Akustik e.V.}, address = {Berlin}, year = {2025}, subject = {Soundscape}, language = {en} } @inproceedings{VersuemerBlaettermannSteffens2025, author = {Vers{\"u}mer, Siegbert and Bl{\"a}ttermann, Patrick and Steffens, Jochen}, title = {Nonlinearities in generalized models based on different soundscape datasets [Abstract]}, series = {DAS|DAGA 2025: 51st Annual Meeting on Acoustics, March 17-20, 2025, Copenhagen}, booktitle = {DAS|DAGA 2025: 51st Annual Meeting on Acoustics, March 17-20, 2025, Copenhagen}, publisher = {Deutsche Gesellschaft f{\"u}r Akustik e.V.}, address = {Berlin}, year = {2025}, subject = {Soundscape}, language = {en} } @phdthesis{Versuemer2025, author = {Vers{\"u}mer, Siegbert}, title = {Generalized prediction of quiet indoor soundscapes based on retrospective and in-situ judgements}, publisher = {Berlin}, address = {Technische Universit{\"a}t Berlin}, doi = {10.14279/depositonce-23962}, pages = {199}, year = {2025}, abstract = {This dissertation aims to enhance the understanding of how people perceive and react to everyday sounds, particularly in their homes. The focus is laid on indoor soundscapes and the interplay between acoustic measures, individual differences, and contextual factors. A retrospective online study and a field study at peoples' homes based on the Experience Sampling Method were the ecologically valid ground truth for four key publications. These address significant gaps in soundscape research by providing insights into the factors influencing sound perception in real-life contexts, the evaluation of low-level (i.e., quiet) sounds, and the consequences of (in)appropriate statistical analysis of imbalanced hierarchical soundscape data. The studies reveal that the sound source category is a critical predictor of annoyance and the pleasantness of soundscapes, with different types of sounds (e.g., natural, human, technical) having distinct impacts. Contrary, the effect of acoustic measures like perceived and calculated loudness on sound perception was expected to be high but was masked by contextual factors. These were the perceived control over the acoustic situation and the affective state of a person in the specific situation, proving context-related perceptual measures to be more important than the sound itself. The research consequently highlights the need for automatic sound source identification in complex polyphony everyday sound environments and suggests that individual preferences and liking of sounds could be potential factors in predicting individual sound perception. The dissertation also emphasizes the importance of using appropriate statistical methods, including mixed-effects models and nonlinear regression techniques, to generate more generalizable and more valid results based on hierarchical and imbalanced soundscape data. The findings underscore the limitations of traditional acoustic metrics and advocate for the use of time-series data to better capture the dynamic nature of everyday sound environments in contrast to stimuli typically used in laboratory studies. The author further developed a multi-objective function for avoiding both over- and underfitting during hyperparameter tuning, significantly improving generalized model fitting in soundscape research. Overall, this work contributes to the field of soundscape research by providing a comprehensive analysis of sound perception in indoor environments, highlighting the importance of context, individual differences, and advanced statistical methods in understanding and modeling soundscapes. Finally, future perspectives were discussed, such as the focus on individual preferences, experiences, and expectations for the improved prediction of individual sound perception.}, subject = {Psychoakustik}, language = {en} } @misc{RosenthalVersuemerBlaettermann2024, author = {Rosenthal, Fabian and Vers{\"u}mer, Siegbert and Bl{\"a}ttermann, Patrick}, title = {flexcv: Easy and flexible nested cross validation for tabular data in python}, edition = {Version v24.0-beta}, publisher = {Zenodo}, address = {Genf}, doi = {10.5281/zenodo.10160846}, year = {2024}, abstract = {Python package customizing nested cross validation for tabular data.}, subject = {Software}, language = {en} } @inproceedings{ErdmannVersuemerSteffens2024, author = {Erdmann, Matthias and Vers{\"u}mer, Siegbert and Steffens, Jochen}, title = {Advanced Soundscape Search: A Web Application for Interactive Exploration of ISO 12913 Datasets [Vortrag]}, series = {Fortschritte der Akustik - DAGA 2024, 18. - 21. M{\"a}rz 2024, Hannover}, booktitle = {Fortschritte der Akustik - DAGA 2024, 18. - 21. M{\"a}rz 2024, Hannover}, publisher = {Deutsche Gesellschaft f{\"u}r Akustik e.V.}, address = {Berlin}, isbn = {978-3-939296-22-5}, pages = {1417 -- 1420}, year = {2024}, abstract = {The development of the ISO 12913 has led to the creation of standardized methodologies for collecting and analyzing individual responses regarding acoustic environments in context, with the aim of enabling comparability, replicability, and the development of modelling algorithms in soundscape prediction and design tasks. The development of methods to represent and explore soundscape data has the potential to facilitate deeper insights into different datasets. Although it is unlikely that any single method will sufficiently capture all information in empirical studies, attempts are worthwhile to facilitate advancements in this realm. Therefore, we propose a web application that fosters an interactive exploration of datasets based on the ISO 12913. The application facilitates a comprehensive soundscape search using the 8 items of the standard, 8 features characterizing the soundscape (e.g., intensities of natural, human, and technical sound sources heard), and 10 distinct acoustic features. The search encompasses all possible combinations of these components, thus facilitating detailed exploration, offering an in-depth dataset overview, and enabling the comparison of different datasets. Further functionalities include text searching and the option to download, save, and load selected soundscapes, enhancing control and flexibility in the design of empirical studies and supporting urban planners in understanding various soundscape items.}, language = {en} } @inproceedings{VersuemerSteffens2024, author = {Vers{\"u}mer, Siegbert and Steffens, Jochen}, title = {Investigating real indoor soundscapes and their predictability for known and unknown subjects [Vortrag]}, series = {Fortschritte der Akustik - DAGA 2024, 18. - 21. M{\"a}rz 2024, Hannover}, booktitle = {Fortschritte der Akustik - DAGA 2024, 18. - 21. M{\"a}rz 2024, Hannover}, publisher = {Deutsche Gesellschaft f{\"u}r Akustik e.V.}, address = {Berlin}, year = {2024}, abstract = {Understanding people's perception of everyday sound involves a complex interplay of various acoustic and non-acoustic factors. Our objective is to uncover important predictors for predicting real indoor soundscapes. To this end, we re-analyzed soundscape data recorded and evaluated by individuals in their homes, aiming for the utmost ecological validity. Given the intricate nature of sound perception and potential non-linear effects of acoustic and psychoacoustic predictors, we utilized machine-learning methods combined with hierarchical linear modeling to analyze 6375 soundscapes from 96 participants including acoustical, psychoacoustical, as well as situational und person-related predictors. Based on this analysis, we measured both the variability within and between subjects and obtained model fits for the prediction of both soundscape pleasantness and eventfulness. In order to discuss cases where predictions for known individuals or places are of interest, we employed (nested) cross-validation using different data-splitting methods. By doing so, our study sheds light on the generalizability of empirical findings when predicting soundscape evaluations for unknown or known subjects and thus supports a deeper understanding of everyday sound perception.}, language = {en} } @inproceedings{RosenthalBlaettermannVersuemer2024, author = {Rosenthal, Fabian and Bl{\"a}ttermann, Patrick and Vers{\"u}mer, Siegbert}, title = {flexcv: Python package for fitting, comparing, and logging multiple machine learning models using various cross-validation methods [Poster]}, series = {Fortschritte der Akustik - DAGA 2024, 18. - 21. M{\"a}rz 2024, Hannover}, booktitle = {Fortschritte der Akustik - DAGA 2024, 18. - 21. M{\"a}rz 2024, Hannover}, publisher = {Deutsche Gesellschaft f{\"u}r Akustik e.V.}, address = {Berlin}, year = {2024}, abstract = {The evaluation of listening experiments and studies on acoustics not only requires basic knowledge of statistics, but also poses challenges in the implementation of different methodologies. Especially for small sample sizes and peculiarities regarding hierarchical data structures, the need to individualize evaluation scripts arises. Therefore, we introduce flexcv, a powerful machine learning package for Python for evaluating various models on experimental tabular data, especially with small sample sizes. It supports random effects evaluation (including random slopes) for both linear and non-linear regressors, providing broad applicability to different experiments and research questions.flexcv quickly allows to perform nested cross-validation on a variety of models for comparison with each other. On the one hand, the implementation of a flexible interface simplifies the exchange of methods in the script, allowing researchers to change cross-validation methods without having to touch the actual cross-validation code. On the other hand, extensive online logging allows and simplifies the evaluation and experiment tracking along the process and different machines.}, language = {en} } @article{VersuemerBlaettermannRosenthaletal.2025, author = {Vers{\"u}mer, Siegbert and Bl{\"a}ttermann, Patrick and Rosenthal, Fabian and Weinzierl, Stefan}, title = {A comparison of methods for modeling soundscape dimensions based on different datasets}, series = {The Journal of the Acoustical Society of America}, volume = {157}, journal = {The Journal of the Acoustical Society of America}, number = {1}, publisher = {AIP Publishing}, issn = {1520-8524}, doi = {10.1121/10.0034849}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-48849}, pages = {234 -- 255}, year = {2025}, abstract = {Soundscape studies vary considerably in study design, statistical methods, and model fit metrics used. Due to this confounding of data and methods, it is difficult to assess the suitability of statistical modelling techniques used in the literature. Therefore, five different methods and two performance metrics were applied to three existing soundscape datasets to model soundscape Pleasantness and Eventfulness based on seven acoustic and three sociodemographic predictors. Datasets differed in soundscape type (urban outdoor vs indoor), experimental setting (field- vs lab-based), size, and study design (site- vs person-centered). The fixed-effects and mixed-effects methods ranged from linear to nonlinear regression based on advanced machine learning approaches. Results showed that models performed better for Eventfulness than for Pleasantness in most cases, while performance as measured by the out-of-sample R2 was dependent on the total variance of the target, especially in both field studies with imbalanced targets and groups. Nonlinear methods consistently outperformed linear regression, with random forest and extreme gradient boosting performing particularly well, while the performance levels of all nonlinear methods remained comparable. Mixed-effects models provided a more generalized, albeit slightly smaller prediction performance when tested on unknown groups. Finally, this study motivates the use of cross-validation with special splitting for analyzing small imbalanced datasets.}, subject = {Akustische Eigenschaft}, language = {en} } @inproceedings{VersuemerBlaettermann2024, author = {Vers{\"u}mer, Siegbert and Bl{\"a}ttermann, Patrick}, title = {Predicting real indoor soundscapes based on auditory and non-auditory factors across different loudness ranges with linear and nonlinear models}, series = {INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Conference Proceeding 8, 4 October 2024}, booktitle = {INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Conference Proceeding 8, 4 October 2024}, publisher = {Institute of Noise Control Engineering}, doi = {10.3397/IN_2024_3386}, pages = {3882 -- 3892}, year = {2024}, subject = {Soundscape}, language = {en} } @article{VersuemerSteffensWeinzierl2023, author = {Vers{\"u}mer, Siegbert and Steffens, Jochen and Weinzierl, Stefan}, title = {Day-to-day loudness assessments of indoor soundscapes: Exploring the impact of loudness indicators, person, and situation}, series = {The Journal of the Acoustical Society of America}, volume = {153}, journal = {The Journal of the Acoustical Society of America}, number = {5}, publisher = {Acoustical Society of America (ASA)}, issn = {0001-4966}, doi = {10.1121/10.0019413}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-46127}, pages = {2956 -- 2972}, year = {2023}, abstract = {This study investigates loudness perception in real-world contexts using predictors related to the sound, situation, or person. In the study, 105 participants recorded 6594 sound environments in their homes, which were then evaluated based on the Experience Sampling Method. Hierarchical linear regressions using a loudness level based on ISO 532-1 allowed for obtaining the best model fits for predicting perceived loudness and explaining the highest variance. LAeq and LAF5 provided comparable results and may require less computational effort. However, the analysis shows that only one-third of the variance explained by fixed effects was attributable to the loudness level. Sixteen percent stemmed from perceived properties of the soundscape; 1\% were attributable to relatively temporally stable, person-related predictors like participants' age; non-auditory situational predictors made no additional contribution. The results thus did not confirm previous findings on loudness perception under laboratory conditions, emphasizing the importance of the situational context. Along with the current paper, a comprehensive dataset, including the assessed person-related, situational, and sound-related measures as well as LAeq time-series and third-octave spectrograms, is provided to enable further research on sound perception, indoor soundscapes, and emotion.}, subject = {Lautwahrnehmung}, language = {en} } @misc{VersuemerSteffensRosenthal2023, author = {Vers{\"u}mer, Siegbert and Steffens, Jochen and Rosenthal, Fabian}, title = {Extensive crowdsourced dataset of in-situ evaluated binaural soundscapes of private dwellings containing subjective sound-related and situational ratings along with person factors to study time-varying influences on sound perception - research data}, edition = {V.01.1}, address = {Zenodo}, doi = {10.5281/zenodo.7193937}, year = {2023}, abstract = {The soundscape approach highlights the role of situational factors in sound evaluations; however, only a few studies have applied a multi-domain approach including sound-related, person-related, and time-varying situational variables. Therefore, we conducted a study based on the Experience Sampling Method to measure the relative contribution of a broad range of potentially relevant acoustic and non-auditory variables in predicting indoor soundscape evaluations. Here we present the comprehensive dataset for which 105 participants reported temporally (rather) stable trait variables such as noise sensitivity, trait affect, and quality of life. They rated 6.594 situations regarding the soundscape standard dimensions, perceived loudness, and the saliency of its sound components and evaluated situational variables such as state affect, perceived control, activity, and location. To complement these subject-centered data, we additionally crowdsourced object-centered data by having participants make binaural measurements of each indoor soundscape at their homes using a low-(self-)noise recorder. These recordings were used to compute (psycho-)acoustical indices such as the energetically averaged loudness level, the A-weighted energetically averaged equivalent continuous sound pressure level, and the A-weighted five-percent exceedance level. This complex hierarchical data can be used to investigate time-varying non-auditory influences on sound perception and to develop soundscape indicators based on the binaural recordings to predict soundscape evaluations.}, subject = {soundscape}, language = {en} } @incollection{RosenthalVersuemerSteffens2022, author = {Rosenthal, Fabian and Vers{\"u}mer, Siegbert and Steffens, Jochen}, title = {Audioinhaltsanalyse und Multilevelmodellierung zur Vorhersage der Bewertung von Indoor Soundscapes}, series = {Deutsche Jahrestagung f{\"u}r Akustik (DAGA)}, booktitle = {Deutsche Jahrestagung f{\"u}r Akustik (DAGA)}, publisher = {DAGA}, address = {Stuttgart}, year = {2022}, language = {de} } @inproceedings{VersuemerSteffensBlaettermann2022, author = {Vers{\"u}mer, Siegbert and Steffens, Jochen and Bl{\"a}ttermann, Patrick}, title = {Subjektive Lautheitsbewertung unter Einfluss situativer und personenbezogener Faktoren}, series = {Deutsche Jahrestagung f{\"u}r Akustik (DAGA)}, booktitle = {Deutsche Jahrestagung f{\"u}r Akustik (DAGA)}, address = {Stuttgart}, year = {2022}, language = {de} } @article{VersuemerSteffensBlaettermannetal.2020, author = {Vers{\"u}mer, Siegbert and Steffens, Jochen and Bl{\"a}ttermann, Patrick and Becker-Schweitzer, J{\"o}rg}, title = {Modelling evaluations of low-level sounds in everyday situations using linear machine learning for variable selection}, series = {Frontiers in Psychology}, volume = {11}, journal = {Frontiers in Psychology}, publisher = {Frontiers}, issn = {1664-1078}, doi = {10.3389/fpsyg.2020.570761}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-23779}, year = {2020}, language = {en} }