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Sound Studies
An Interdisciplinary Journal
Volume 5, 2019 - Issue 2
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Sound Reviews

The drum machine’s ear: XLN Audio’s drum sequencer XO and algorithmic listening

 

Notes

1. Goldmann had just published his collection of interviews on the topic: Presets – Digital Shortcuts to Sound (Goldmann Citation2015).

2. Cf. Future Music Magazine Citation2012; the interview with Stefan Goldmann was published in Das Filter, cf. Kobel and Goldmann Citation2015.

3. Bergling says: “I’ve never been very technical at all […]. [But] if I tweak this [moves the cursor of the mouse; MK] it sounds good, I’ve always been [working] more like that”; i.e. intuitively and by ear (Future Music Magazine Citation2012, min. 24:20).

4. The drum sampler Atlas released in 2018 by Algonaut already promised to change the processes of drum sequencing by similarly visualising drum packs. Like XO, Atlas works with a machine learning algorithm that analyses and orders drum sounds “based on style and character” (cf. Algonaut Citation2018).

5. It might of course be interesting to know how the algorithm discriminates and functions: is it timbral characteristic, style, genre, intensity or morphology of a sound sample that structures the ordering?

6. Algorithmic listening and machine listening are both terms that are beginning to circulate in the fields of sound and media studies, cf. Miyazaki Citation2013; also cf. the research network “Humanising Algorithmic Listening” (http://www.algorithmiclistening.org/) and Technosphere Magazine’s special issue on “Machine Listening” (“Machine Listening” Citation2018).

7. Cf. The neologism rhythmachine stems from Kodwo Eshun’s writings in More Brilliant Than The Sun (Eshun Citation1998) and might denote a rhythmic feel/knowing/doing/grooving specific to the drum machine; also see Malte Pelleter for a further theorisation of the notion of the rhythmachinic (Pelleter Citation2018).

8. XO functions here of course only as one example of such algorithmic listening and organising of sound: we might furthermore think here of algorithmic listening that is performed in streaming platforms such as Spotify, automated mastering tools such as Landr or more generally preset sounds in DAWs.

9. Cf. Thompson Citation2017 for the debate around sonic materialism and ontologies of sound which have been happening in the fields of sound studies more recently.

Additional information

Notes on contributors

Malte Kobel

Malte Kobel is a TECHNE/AHRC-funded doctoral student in Music at Kingston University London. His PhD project attempts a theorisation of the singing voice from the perspective of listening: working through philosophies of voice, musicology, media theory and sound studies. Malte has studied musicology at the University of Vienna (BA) and at Humboldt-University of Berlin (MA).

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