Visualizing the soundscape: an approach at the interface of music and ecologyVisualiser le paysage sonore : une approche à la croisée de la musique et de l'écologie

Adèle de Baudouin, Jérôme Sueur et Pierre Couprie

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Résumés   

Index   

Index de mots-clés : Paysage sonore, Écoacoustique, Électroacoustique, Visualisation sonore, Transdisciplinarité, Écoféminisme.
Index by keyword : Soundscape, Ecoacoustics, Electroacoustic, Sound visualization, Transdisciplinarity, Ecofeminism.

Plan   

1. Introduction

1The concept of soundscape emerged with the World Soundscape Project at the end of the 60’s with the desire to draw attention to the sonic environment. This idea comes from the awareness of ecological issues in a Western socio-cultural context. The soundscape is located at the intersection of ecology, acoustics and music (Schafer R. Murray, 1977; Truax Barry & Westerkamp Hildegard, 2006). Following these initial perspectives, the electroacoustic musical genre considers the soundscape as “an environment of sound (or sonic environment) with emphasis on the way it is perceived and understood by the individual, or by a society. It thus depends on the relationship between the individual and any such environment. The term may refer to actual environments, or to abstract constructions such as musical compositions and tape montages, particularly when considered as an artificial environment (Truax Barry, 1999). This definition of soundscape supports the idea that soundscapes are expressions of the environment perceived or constructed by the listener. This idea is further developed in the words of Hildegard Westerkamp: “soundscape as a language with which places and societies express themselves” (Westerkamp, Hildegard, 1996). In ecology, a soundscape is an assemblage of sounds emanating from a landscape that can be analyzed and decomposed to get access to information about ecological patterns and processes (e.g.  Pijanowski, Bryan C. et. al., 2011). In ecoacoustics, the discipline that studies biodiversity through the lens of sound, a soundscape is commonly decomposed into three categories: the biophony, which includes all biotic sounds, the geophony, which refers to natural but abiotic sounds, and the anthropophony, which groups all sounds produced by human activities (Sueur Jérôme & Farina Almo, 2015).

2At the crossroads of musicology and ecology, the soundscape is situated from a specific point of observation, in a socio-cultural context and with the objective of describing a facet of the environment. Here, we propose a new interpretation of the soundscape (Figure 1). Musical and ecological soundscapes are the result of a constant and non-hierarchical interaction between (1) sound material, (2) acoustic space, and (3) type of composition, with the intention of representing an environment.

Figure 1: The concept of soundscape binding both musical and ecological approaches.

3In the context of the current biodiversity decline and ecosystem functioning disruption, soundscapes can help in raising awareness of environmental problems by “linking inner and outer worlds” (Westerkamp Hildegard, 1999). Understanding the musicological and ecological information soundscapes content is therefore a major challenge. The analysis of composed and natural soundscapes are both challenging because, on one hand, there is little documentation explaining the process of soundscape creation (Mancero Baquerizo Daniel, 2019), and, on the other hand, the dynamics of nature soundscapes are still difficult to track and understand (Sueur Jérôme & Farina Almo, 2015). Few tools have been proposed to visualize soundscapes and none of them have been tested in both music and ecology. Both electroacoustic and ecoacoustics need sound visualization to navigate through, analyze, and share audio samples (Towsey Michael, 2014; Couprie Pierre, 2015 ; Couprie Pierre, 2018a ; Phillips Yvonne F., 2018) (Figure 2). The spectrogram is the most usual and direct time-frequency-amplitude representation used in both disciplines. In ecoacoustics, recent development suggested original displays such as long-term spectrograms, false-color spectrograms based on acoustic indices, sound element polar histograms and species diel plot (Phillips Yvonne F., 2018). At the same time, electroacoustic developed Self-Similarity Matrix (SSM), Brightness Standard Deviation (BStD), and arc diagram solutions (Couprie Pierre, 2015 ; Wattenberg Martin, 2002).

Figure 2: Ecoacoustics and electroacoustic workflows both need to sound visualizations.

4In this paper, we introduce a transdisciplinary approach, crossing the tools developed in the two disciplines and proposing a new one, the Frequency Band Waveform (FBW). We applied this transdisciplinary approach to a women’s corpus of soundscape compositions, a major corpus but rarely included in music analyses.

2. A Soundscape corpus

5We have selected soundscapes varying in their links to ecoacoustics or electroacoustic (Table 1). This corpus is produced by women composers perceived with white ethnic origins, from Western countries and mainly working in territories with a colonial history. These women composers offer various versions of talking about natural environments, through their approach of the field, their use and transformation of sound material, their background, their relationship to sound and their discourse. The analysis of their works will be done considering our own social, racial and economic situation.

Table 1: Soundscape corpus main information.

2.1. Beneath the Forest Floor

6Beneath the Forest Floor was composed by Hildegard Westerkamp in 1992 and received a mention at Prix Italia 1994. Hildegard Westerkamp (1946 - ) is a soundscape composer, soundmaker, and educator. She was born in Germany and emigrated to Canada in 1968, where she lives in British Columbia, on the ancestral lands of the Coast Salish peoples. Her work is part of the acoustic ecology movement, of which she is one of the main investigators. Through her works she proposes to pay “attention to the act of listening itself, to the inner, hidden spaces of the environments we inhabit and to details both familiar and foreign in the acoustic environment” (Westerkamp Hildegard, 1996). Through her experience of a place, she confronts the listener with cultural and social questions (Duhautpas, F., and Solomos, 2014), mainly of feminist and ecological issues. Beneath the Forest Floor is a piece composed “of sounds recorded in the old growth forests of the west coast of British Columbia. It moves us through the visible forest, into its’ shadow world, its’ spirit; into that which effects our body, heart and mind when we experience forest” (Westerkamp Hildegard, 1996). This very old Sitka spruce (Picea sitchensis) and cedar (Cedrus sp.) forest is inhabited by “small songbirds, ravens and jays, squirrels, flies and mosquitoes” (Westerkamp Hildegard, 1996) and was already half destroyed by logging operations during the sound recording sessions during the summer of 1991. This piece was commissioned by CBC Radio for Two New Hours and was produced in CBC’s Advanced Audio Production Facility. We worked on a two channel audio file (17’23”) in .wav format.

2.2. Ci(r)cadian Rhythm

7Ci(r)cadian Rhythm was composed by Yulia Glukhova in 2019 and received the Soundscape - Field recordings award from Phonurgia Nova Awards 2019¹. Yulia Glukhova (1989 - ) is a Russian sound artist based in Moscow. She works on sound with different approaches such as sound design for film, experimental electronic music, technological art and field recording. Through her works she proposes a sense of place to listeners (French Jez riley, 2018). She considers sounds of nature as sound effects and uses them for their “particularity [...], logic of its development and emotion it awakes by itself” (French Jez riley, 2018) (Glukhova Yulia, 2019). Ci(r)cadian Rhythm refers to the circadian rhythm, a term mainly used to describe the biological cycles of the human body over a 24-hour cycle. Here, the composer traces a “full day cycle reduced to half an hour, recorded in the Crimean Peninsula during a solitary trip in the summer of 2018. The sound activity of insects (mainly crickets and cicadas) is indexed to the ambient temperature: it is a sensory marker of the environment and a biological clock” (Glukhova Yulia, 2019). The sound recordings were made by the composer during a solo trip in the summer of 2018. This piece was self-produced and initially designed for an octophonic installation. We worked on a two channel audio file (36’51”) in .wav format.

2.3. Timelapse Jura 01052019

8Timelapse Jura 01052019 was composed by Adèle de Baudouin in 2023. Adèle de Baudouin is a researcher working at the crossroads of ecoacoustics and electroacoustic and a composer. As an electroacoustic composer, she is interested in exploring the boundaries that humans dictate to natural environments and non-human living beings. Through her creations and her research work, she aims at raising public awareness of listening to and preserving soundscapes in all their forms. Timelapse Jura 01052019 is a sound time-lapse of one day in the Risoux forest made for the purpose of scientific mediation to show the biophony evolution of the soundscape. Risoux forest is a temperate cold climax forest located in the French Jura Mountains close to Switzerland. The forest is characterized by mid-mountain vegetation dominated by the European spruce (Picea abies). The forest is inhabited by a rich animal diversity, including key species such as the European lynx (Lynx lynx), the Grey wolf (Canis lupus), and the Western Capercaillie (Tetrao urogallus). The Risoux forest is crossed by 26 km of roads, hiking and cross-country skiing trails and is overflown by aircraft corridors. This strong human presence is accentuated by hunting and commercial logging. Recordings were obtained using autonomous recording units (Songmeter SM4, Wildlife Acoustics Inc., Concord, MA, USA), each equipped with two omnidirectional microphones. The recorders were programmed to record 1 min every 15 min (1’ on, 14’ off). Audio recordings were saved under uncompressed .wav format with a 44.1 kHz sampling frequency, 16-bit depth and 16 dB gain. These recordings were part of long-term ecoacoustic programs which started in July 2018 in the Risoux forest [17]. The piece was made by assembling the first ten seconds of the first minute of recording of each hour of 1st May 2019 using the R package seewave (Sueur Jérôme et. al., 2008). A 500 Hz high-pass filter was applied with Ocenaudio (release 3.11.12) to focus the listening and analysis on the biophony. We worked on a mono channel audio file (04’00”) in .wav format.

3. Features and representations

3.1. Audio descriptors and acoustic indices

9In music analysis, audio descriptors are used to characterize the audio spectrum along time. These descriptors were originally developed for the classification of large audio databases (Music Information Retrieval) but can be used in other contexts such as automatic composition, music education or music analysis (Couprie Pierre, 2022 ; Lerch Alexander, 2023). These tools have been used mainly to analyze classical or popular music, more rarely to describe electroacoustic pieces and even less soundscape compositions. The root-mean-square (RMS) calculates the quadratic mean of audio samples (Lerch Alexander, 2023). It can be calculated over a time sliding window so that it can reveal time x amplitude events such as attacks, morphological evolutions and ruptures (Couprie Pierre, 2018b).

10The spectral flux (SF) measures the amount of change of the spectral shape (Lerch Alexander, 2023). Revealing spectral roughness, this descriptor is particularly relevant when the spectral changes over time are low (Couprie Pierre, 2016).

11The zero crossing rate (ZCR) counts the number of times where the signal crosses the zero axis (Lerch Alexander, 2023). This can be used to reveal the density and spectral complexity of materials (Couprie Pierre, 2018b).

12In ecoacoustics, acoustic indexes have been developed to estimate diversity within a recording (α indices) or to compare diversity between recordings (β indices) (Sueur Jérôme et. el., 2014). The acoustic indices derived from biodiversity indices, which are mathematical functions developed to assess aspects of biodiversity (e.g. richness, evenness, divergence) (Magurran Anne E. & Brian J. McGill, 2010; Sueur Jérôme, 2018). Acoustic indices extract data from sound to obtain rapid and quantifiable information on long-term soundscapes. The Acoustic Complexity Index (ACI) was coined to assess biophony level. Based on the short-term Fourier transform, this index estimates the change of amplitude across frequency samples (Farina Almo et. al., 2011; Pierretti et. al., 2011).

13The spectral entropy (H) measures the Shannon evenness of the frequency spectrum based on the hypothesis that a rich and balanced soundscape should lead to an evenly distributed frequency spectrum. The index can be computed along time according to a sliding window (Sueur Jérôme, 2018).

3.2. Soundscape Chord Diagram (SCD)

14The Soundscape Chord Diagram is a circular similarity representation that can be applied to any type of soundscape, either in electroacoustic or in ecoacoustics (de Baudouin Adèle et. al., 2024). The SCD is based on a β ecoacoustic index, namely (Lellouch Laurent, 2014), which compares two-by-two the similarity between cumulative frequency spectra of sound fragments. The index was computed using the R package seewave (Sueur Jérôme et. al., 2008). The coloration of the arcs was automatically determined through a cluster analysis based on an hierarchical clustering analysis (HCA) on the mean frequency spectrum from each fragment. The clusters were determined using the HCPC function of the R package FactoMineR (Lê Sébastien et. al., 2008).

15The SCD computed on Beneath the Forest Floor revealed four sections: (1) from 00:00 to 05:00 and from 10:30 to 11:00; (2) from 05:00 to 07:30; (3) from 07:30 to 09:00 and from 13:00 to 17:00; and (4) from 09:00 to 13:00 (Figure 3). This structure corresponded well with the analysis proposed by F. Duhautpas, A. Freychet and M. Solomos based on analytical descriptions (2015) : part (1) from 00:00 to 04:39; part (2) from 04:39 to 07:30; part (3) from 07:30 to 08:43; part (4) 08:43 to 13:10; and part (5) 13:10 to 17:23. The only difference is that the SCD combined parts (3) and (5) in a single section, highlighting their very strong spectral similarities.

16The SCD computed on Ci(r)cadian Rhythm revealed three sections: (1) from 00:00 to 12:00, from 14:00 to 21:00 and from 27:00 to 28:00; (2) from 21:00 to 25:00; and (3) from 12:00 to 14:00 and from 25:00 to 36:00 (Figure 3). An analysis based on listening by one of us (ADB) suggests another division: part (1) 00:00 to 10:27 corresponding to the night marked by the song of crickets; part (2) 10:27 to 17:33 for the beginning of the day with light songs of orthopterans; and part (3) 17:33 to 24:57 with a rise in sound density evoking the hottest hours of the day where notably the cicadas rise in power and part (4) 24:57 to 36:51 with a return to calm and gradual appearance of a nocturnal atmosphere. The difference between the SCD and the human interpretation can be partly explained by the strong transformations of the raw materials made by the composer. The general form evokes a day and can be interpreted as such by ear, but the spectral analysis of the sound material revealed a structuring more connected to the work done on the material by the composer.

17The SCD computed on Timelapse Jura 01052019 revealed three sections: (1) a night period mostly located from 22:00 am to 05:00 am; (2) a dawn period from 06:00 am to 10:00 am and dusk period from 20:00 am to 22:00 pm; and (3) a day period mostly located from 10:00 pm to 20:00 pm (Figure 3). The piece follows the circadian cycle and translates the sound changes of a Spring day in a Jura forest. In addition, the SCD revealed atypical elements such as the one from 02:00 am to 03:00 am which shares more similarity with the daily period than the night period. This segment corresponded to the song of a Tengmalm’s owl (Aegolius funereus). This sound element has a spectral structure closer to the daytime segments, marked by light bird song, than to the nighttime segments, which are noisy and have no clear frequency distribution.

Figure 3: Soundscape chord diagrams (SCDs) of the three pieces of the soundscape corpus. Each SCD shows the acoustic similarity within the soundscape composition. The beginning is positioned in the North direction (0°) and time runs in a clockwise manner for a total duration of the piece. The size of circular arcs and the number of links between segments are proportional to spectral similarity computed with the spectral index (1-Dcf)). Colors correspond to the clusters automatically found by the hierarchical clustering analysis (HCA). From top to bottom: Beneath the Forest Floor by Hildegard Westerkamp (contiguous segments of 30 sec, HCA partition with four clusters, links with a similarity below 0.9 not shown), Ci(r)cadian Rhythm by Yulia Glukhova (contiguous segments of 1 min, HCA partition with three clusters, links with a similarity below 0.8 not shown), Timelapse Jura 01052019 by Adèle de Baudouin (contiguous segments of 10 sec, HCA partition with three clusters, links with a similarity below 0.8 not shown). Colors correspond to the clusters automatically found by the hierarchical clustering analysis (HCA). From top to bottom: Beneath the Forest Floor by Hildegard Westerkamp (contiguous segments of 30 sec, HCA partition with four clusters, links with a similarity below 0.9 not shown), Ci(r)cadian Rhythm by Yulia Glukhova (contiguous segments of 1 min, HCA partition with three clusters, links with a similarity below 0.8 not shown), Timelapse Jura 01052019 by Adèle de Baudouin (contiguous segments of 10 sec, HCA partition with three clusters, links with a similarity below 0.8 not shown)."

3.3. Brightness Standard Deviation (BStD)

18Brightness Standard Deviation is a representation originally developed to visualize the evolution of timbre in musical works (Malt Mikhail, 2015). Three audio descriptors are combined to constitute a single curve (Y, thickness and color) and allows the visualization of morphologies and formal structures (Couprie Pierre, 2015). The choice of these uncorrelated audio descriptors depends on the piece being analyzed and the information to be shown. Here, we used RMS, SF and ZCR, commonly used in music analysis. These indices were computed directly in iAnalyse 5. We also used ACI and H indices. These two indexes were computed using the R package seewave (Sueur et al., 2008) then the data imported into iAnalysis. To our best knowledge, BStD has never been previously used on ecoacoustic soundscape.

19We generated a BStD with audio descriptors from musicology on the piece of the corpus Timelapse Jura 01052019 composed from automatic ecological recordings (Figure 4). This representation reveals three parts and two transitions between 01’00’’ and 01’30’’ (i.e. 06:00 and 09:00) then between 03’10’’ and 03’40’’ (i.e. 19:00 and 22:00). The first event outlined in grey between 00’20’’ and 00’30’’(i.e. 02:00 and 03:00) corresponds to the song of an owl during the night (see section 3.2). The daily cycle is thus revealed by an evolution of the spectrum in mirror. In addition, it was possible to identify passages of transition where the amplitude increases slightly and varies and where the material becomes more complex with a stronger ZCR (circled in gray). In other words, these passages corresponded to the morning and evening bird chorus.

3.4. Frequency Band Waveform (FBW)

20Frequency Band Waveform is a new multipanel representation of a time wave that displays oscillograms according to a frequency band. The amplitude scale, color and number of these bands can be set up. A frequency band normalization is automatically applied to allow better visibility of the weakest sound information. This tool is based on the Acoustic Niche Hypothesis (ANH) which assumes that each species occupies a specific acoustic niche in the acoustic environment so that interferences between species are minimized (Krause Bernie, 1993). This representation is available in iAnalysis 5 and seewave.

21The FBW was applied to a section at the end of Ci(r)cadian Rhythm when nocturnal sonorities arise (Figure 5). The frequency band from 0 Hz to 100 Hz corresponded to the background noise of natural sound environments, which can be observed on many field recordings. The second frequency band from 100 Hz to 2500 Hz highlighted low and short elements corresponding to the call of a dog. The frequency band from 2500 Hz to 3500 Hz marked a cricket stridulation (Oecanthus sp.). The frequency band from 3500 Hz to 6500 Hz covers bird songs, in particular the flight calls of Common Swift (Apus apus). The 6500-13000 Hz frequency band underlines the constant and repetitive presence of orthoptera.

3.5. Self-Similarity Matrix (SSM)

22Self-Similarity Matrix is a 2-D similarity representation developed to visualize the time structure and to highlight the singularities of musical works (Couprie Pierre, 2015 ; Couprie Pierre, 2022 ; Foote Jonathan & Cooper Matthew, 2002). The SSM represents the distance between all the values computed from the FFT on a matrix. The coloration is determined by the Manhattan distance from the matrix in a pseudo-color gradient. The time course is represented on the two axes X and Y, so the matrix is symmetrical in its diagonal. To our best knowledge, SSM has never been previously used on natural soundscape and rarely on soundscape compositions.

23We made an overview of the whole piece Beneath the Forest Floor with a SSM visualization (Figure 6). It proposed a structure in five main parts. The distribution is almost palindromic, revealing this particular work of the composer difficult to identify only with an analysis based on listening. This analysis proposes a different and complementary vision of the evolution of the form than that proposed upstream by the SCD (see section 3.2).

Figure 4: Timelapse Jura 01052019, From top to bottom: BStD (Y: RMS amplitude; depth: spectral flux; color: zero crossing rate) and coloured spectrogram (0-10000 Hz).

Figure 5: Ci(r)cadian Rhythm (32’00’’ to 35’00’’), From top to bottom: FBW (Frequency bands from bottom to top: 0-100 Hz, 100-2500 Hz, 2500-3500 Hz, 3500-6500 Hz, 6500-13000 Hz) and grey level spectrogram (0-13000 Hz).

Figure 6: Beneath the Forest Floor, From top to bottom: coloured spectrogram (0-22000 Hz) and self-similarity matrix (SSM) calculated on Manhattan distance.

Figure 7: Ci(r)cadian Rhythm, From top to bottom: BStD (Y: RMS amplitude; depth: ACI; color: spectral entropy), BStD (Y: RMS amplitude; depth: spectral flux; color: zero crossing rate) and coloured spectrogram (0-22000 Hz).

4. Discussion

24We performed visualization analyses at the interface between music and ecology on several soundscapes differing in sound material, compositional type and acoustic space. As mentioned in the introduction, methods of visualization have already been developed in parallel in electroacoustic and ecoacoustics. Our work denotes by binding together composed and natural soundscapes and studying them with the same tools. This illustrates that there is no strict barrier between the two concepts of soundscapes and that it is possible to describe them under the same principles.

25The BStD applied to a time-lapse of automatic recordings (Timelapse Jura 01052019) underlined the overall structure of the composition and its transitional phases based on biophony dynamics. Timelapse Jura 01052019 is a sound time-lapse of one day in the Risoux forest made for the purpose of scientific mediation to show the biophony evolution of the soundscape. The musical intent of the composer therefore follows the natural time dynamics.

26To further explore the possibilities of the BStD we used musical and biodiversity features on a piece that claims a strong musical intention combining unprocessed and processed sound recordings, Ci(r)cadian Rhythm (Figure 7). The BStD based on musical features revealed strong compositional gestures, hardly identifiable on a classic spectrogram. For example, there is a sudden change between 17’30’’ and 18’30’’ that appears as an important variation of the thickness of the time series indicating a strong irregularity in the spectral flow. The BStD realized with the acoustic indices was more difficult to interpret. However, the ACI index seemed to indicate spectral variety, a dynamic that might be informative for further musicological analysis. Electroacoustic and ecoacoustics both work on a sound material that is spectrally complex and difficult to segment temporally. Both disciplines have developed empirical methods to obtain specific results for each situation. The results provided by audio descriptors such as acoustic indices are subject to interpretation and their results may vary depending on the elements studied (Couprie Pierre, 2022 ; Fuller Susann, 2015). The cross-use of these musical and biodiversity features seems promising and deserves to be further developed by testing different indices and analyzing other types of musical works.

27Both SCDs and SSMs provide a global image and highlight sections that structure the compositions. The various soundscape structures in the corpus reflect the specific vision and work of each composer. Moreover, these images offer a preliminary spectral approach for the form analysis. Other analyses could be undertaken to explore other acoustic aspects such as transitions, timbre, finer structuring proposals.

28With the FBW, we designed a visualization tool based on an ecological theory, the Acoustic Niche Hypothesis, that leads to an original musicological analysis of a soundscape. The FBW clearly depicts the frequency superposition of the different elements of the soundscape and their temporal distribution. These elements correspond to precise choices made during field recording or editing. FBW reveals the technical setting of Yulia Glukhova’s approach, who composed her soundscape in reference to a biological concept, the circadian rhythm, and to the intrinsic emotional value of sounds. The tests carried out with the FBW on soundscapes where the frequency structures were not very marked or where there was constant background noise were less conclusive. This reveals the limits of this tool but also those of the acoustic niche hypothesis which is still controversial (Schmidt Arne K.D., 2016). In music, the FBW tool is recommended for compositions with a clear frequency partitioning.

29Even if the visualization tools here developed do not provide all perceptible information (Roads Curtis, 2016) and that the acoustic space yet remains to be described (see Figure 1), they still reveal the multiplicity of the compositional techniques and the variety of the work of the sound material collected by the composers. Listening remains however an important step of ecoacoustics and is the key of musical analysis and music interpretation. It is crucial, as attempted here, to multiply tools and analyses to embrace composition as a mosaic of interpretations.

30Women and gender minority's electroacoustic works are most often studied from a sociological and philosophical perspective. Here, we propose objective and repeatable tools for a musicological and ecological approach. As we saw earlier, these visualizations provide musical and ecological formal information. They also give access to conceptual aspects of the works, such as the ecological or emotional messages advocated by the composers. This approach needs to be developed further to better understand the musicological and ecological characteristics of soundscapes composed by women and gender minorities.

31Moreover, this method of analysis by corpus seems essential to pursue the development of contextualized methodology and specific visualization tools for soundscape compositions

5. Conclusion and perspectives

32The transdisciplinary approach we have developed at the interface of music and ecology provides efficient tools to visually analyze soundscapes. The analyses developed in this study allow us to work on the structure of the pieces. By pursuing our approach, we would like to explore other aspects such as timbre and transitions. In addition, this cross-transfer of features between ecological sciences and musicology is promising. It needs to be developed further to provide tools that are adapted to soundscapes and easily interpretable. The FBW shows us that it is relevant to transfer theory from ecological sciences to musicology. This type of knowledge transfer provides new possibilities for musical analysis. Using this interdisciplinary approach and the visualization tools it proposes, it is possible to improve our perception of soundscapes.

33Ecofeminisms identify that “there are important historical, empirical, symbolic and theoretical connections between the domination to which women have been subjected and that which has been exercised against nature” (Warren Karen J., 2009). An ecofeminist soundscape is a soundscape that reveals a natural environment and the connections to that environment from a gender minority perspective. We propose to develop a sound ecofeminist approach combining feminist, queer, ecological and decolonial visions, with scientific visualization tools at the interface of music and ecology to provide a framework to better understand soundscapes and our relationship with nature.

34To conclude, we would like to point out that soundscape composers from non-Western countries still need to be studied and highlighted. Their works offer a precious perspective on the ecological and social crisis we are going through.

6. Acknowledgments

35This work was achieved with the support of the Collegium Musicæ (Alliance Sorbonne Université). The work conducted in the Risoux forest was supported by the Parc Naturel Régional du Haut-Jura, which received funding from the Région Bourgogne-Franche-Comté, the Région Auvergne-Rhône-Alpes and the DREAL Bourgogne-Franche-Comté. We warmly thank Marie-Pierre Reynet and Julien Barlet for their support. We are grateful to Fanny Lannoy and Marc Jacquin of Phonurgia Nova for their assistance. We would also like to acknowledge Maxime LeCesne for his advice.

Bibliographie   

Notes   

Citation   

Auteur   

Quelques mots à propos de :  Adèle de Baudouin

Quelques mots à propos de :  Jérôme Sueur

Quelques mots à propos de :  Pierre Couprie