Sonic Specters of a Gathering

One of the first provocations for Sonic Specters of a Gathering was the exploration of various concepts of time. In his book Kitab-Al-Shifa (The Book of Healing), the medieval Persian polymath Ibn Sina contemplates how rocks and mountains near the Amur Darya River in Uzbekistan could have formed. He gestures toward the temporalities in which such geological formations occur, which later was developed and conceptualized as geological or deep time. Deep time brings into play the geological and cosmological time scales that span billions of years. These vast stretches of time extend beyond the clock time that chronologically operates on a human scale. Deep time’s scale brings into consideration the immense age of the universe and the gradual processes of the earth that have shaped it over billions of years. These vast temporal scales became a point of interest for Sonic Specters of a Gathering, as they disrupt the chronological order of clock time and open temporalities that challenge our relationship with the Earth.

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From deep time, we moved toward thinking about objects, beings, and time as they are experienced and conceptualized in a world that is deeply distanced. In our immanent moment, the time of the earth seems to be categorized into specific territorial and clock cartographies that create marginalities, therefore creating invisibilities. In his 1983 book Time and the Other, anthropologist Johannes Fabian introduces »schizogenic time,« which refers to the notion that Western anthropology perceives nonwestern cultures as existing outside of historical time, frozen in an eternal present, which he terms as the »primitive present.« The linear, uniform, and objective understanding of time creates a sense of temporal superiority, projecting nonwestern cultures as temporalities stuck in a perpetually static and frozen existence. Western temporalities, therefore, claim the position of being the masters that can unlock progress and enlightenment, positing a position of rescue for nonwestern temporalities. Schizogenic time challenges this hierarchical view by emphasizing the co-existence of multiple temporalities and the validity of diverse temporal experiences. Fabian argues that all temporalities have different historical and cultural trajectories and may or may not align with each other.

Deep time and schizogenic time problematize our engagement with the Other. Through deep time, the geology and its temporal scales that are othered by the chronologies of clock time appear as a phantom whose time scales are too vast to conceive and comprehend. When considering schizogenic time, nonwestern temporalities stand forth as a gathering that shakes colonial cartographies, national imaginations, history, belonging, and language. Both deep time and schizogenic time aid in understanding an inter-referential existence of beings, ecologies, and objects. Existence appears as an embedded gathering with multiple temporal fields and historical trajectories. In such speculative thinking about earth ecologies as a gathering with an embedded sense of being, time is not strictly chronological, but exists abstractly within objects and their ecologies. They present time as a gathering that disorients clock time. It’s manifested in the echoes of absent elders, in the clamor of the oppressed in riots and uprisings. It pervades cities, bodies of water, mountains, trees, and rocks, primarily existing as a form of gathering – a militant articulation disrupting conventional organizational structures. In this moment of conceiving time as a speculative gathering that disrupts the organized structures, a folk tale about a glorious bird called Lal Muni emerges as another point of direction.

Lal Muni is a miraculous bird that sings for everyone and everything. It sings for rocks, mountains, birds, boulders, people, communities, and languages – all except the king. The king wants Lal Muni to sing about him, but the bird refuses. Unmoved, the bird keeps singing new songs without any mention of the king, and the battle between the two rages. Lal Muni’s tale, apart from addressing the tension between the heretical poet and the sovereign power, also articulates the militant embeddedness of always gathering outside the sovereign power structures. Lal Muni becomes the sonic decipherer of the gathering of time outside of sovereign power. Its songs could never mention the king because it always sang militantly against the state. Lal Muni, therefore, opened a proposition: How could the gathering on earth that we discussed above be speculated sonically as songs of dissent against any sovereign power?

In order to formulate our own Lal Muni, we conceived of writing a machine-learning algorithm based on the structure of a recurrent neural network. After the algorithm was written and set up, we started to collect sonic imprints of gatherings from various times and lands. These convenings were primarily protests, uprisings, and riots against the respective state in which they occurred. We did not limit the sonic data only to slogans and human chants but also included the sounds of breezes, winds, seas, rivers, trees, birds, and so on. After collecting these sounds, the data was de-sonified into special text characters (our  algorithm does not understand sound data but only text-based data, so sound archives were converted). The algorithm then speculated new de-sonified data which was subsequently re-sonified using a Python script. This process created a variety of material ranging from de-sonified sound, data visualization, and text-based data, which all became outcomes and part of the project. The movement of data within the Recurrent Neural Network is not necessarily chronological and unilateral. The data moves forward and backward in the epochs during the training phase. The machine-learning algorithm, akin to Lal Muni, therefore generated diverse outputs such as data visualizations, soundscapes, and abstract poetry, thus speculating a gathering, a protest, or a riot that is yet to happen. It speculates the soundscape through a sonic gathering of voices of the oppressed from different times and spaces. However, it’s crucial to note that this algorithm is not all-encompassing. Employing natural language processing, it doesn’t seek to replicate human intelligence. Instead, it speculates and leans toward abstraction, embedding meanings within these abstract forms rather than producing structured, definitive outcomes.