Selaa lähdekoodia

Update 'content/topic/(against)-the-coming-world-of-listening-machines.md'

master
james 4 vuotta sitten
vanhempi
commit
abe78982e4
1 muutettua tiedostoa jossa 1 lisäystä ja 1 poistoa
  1. +1
    -1
      content/topic/(against)-the-coming-world-of-listening-machines.md

+ 1
- 1
content/topic/(against)-the-coming-world-of-listening-machines.md Näytä tiedosto

@@ -107,7 +107,7 @@ Moreover, because machine listening is so deeply bound up with logics of automat

But machine listening isn't exactly listening either.

Technically, the methods of machine listening are diverse, but they bear little relationship to the biological processes of human audition or psychocultural processes of meaning making. Many are fundamentally [imagistic](https://medium.com/@krishna_84429/audio-classification-using-transfer-learning-approach-912e6f7397bb "Audio classification using transfer learning approach"), in the sense that they work by first transforming sound into spectograms. Many work by combining auditory with other forms of data and sensory inputs: machines that [listen by looking](https://www.wired.com/story/lamphone-light-bulb-vibration-spying/ "Spies Can Eavesdrop by Watching a Light Bulb's Vibrations"), or by cross-referencing audio with geolocation data. In the field of Automatic Speech Recognition, for instance, it was only when researchers at IBM moved away from attempts to simulate human listening towards statistical data processing in the 1970s that the field began making decisive steps forward [^airplanes]. Speech recognition needed to untether itself from "human sensory-motor phenomenon" in order to start recognising speech. Airplanes don't flap their wings. [^airplanes]
Technically, the methods of machine listening are diverse, but they bear little relationship to the biological processes of human audition or psychocultural processes of meaning making. Many are fundamentally [imagistic](https://medium.com/@krishna_84429/audio-classification-using-transfer-learning-approach-912e6f7397bb "Audio classification using transfer learning approach"), in the sense that they work by first transforming sound into spectograms. Many work by combining auditory with other forms of data and sensory inputs: machines that [listen by looking](https://www.wired.com/story/lamphone-light-bulb-vibration-spying/ "Spies Can Eavesdrop by Watching a Light Bulb's Vibrations"), or by cross-referencing audio with geolocation data. In the field of Automatic Speech Recognition, for instance, it was only when researchers at IBM moved away from attempts to simulate human listening towards statistical data processing in the 1970s that the field began making decisive steps forward.[^airplanes] Speech recognition needed to untether itself from "human sensory-motor phenomenon" in order to start recognising speech. Airplanes don't flap their wings. [^airplanes]

Even if machine listening did work by analogising human audition, the question of cognition would still remain. Insofar as "listening" implies a subjectivity, machines do not (yet) listen. But this kind of anthropocentrism simply begs the question. What is at stake with machine listening is precisely a new auditory regime: an analog of Paul Virilio's "sightless vision", [^Virilio] the possibility of a listening without hearing or comprehension, a purely correlative listening, with the human subject decentered as privileged auditor.



Ladataan…
Peruuta
Tallenna