diff --git a/content/topic/(against)-the-coming-world-of-listening-machines.md b/content/topic/(against)-the-coming-world-of-listening-machines.md index 0fb28a1..ec376cb 100644 --- a/content/topic/(against)-the-coming-world-of-listening-machines.md +++ b/content/topic/(against)-the-coming-world-of-listening-machines.md @@ -105,7 +105,7 @@ Scientifically, machine listening demands enormous volumes of data: exhorted, ex Because machine listening is trained on (more-than) human auditory worlds, it inevitably encodes, invisibilises and reinscribes normative listenings, along with a range of more arbitrary artifacts of the datasets, statistical models and computational systems which are at once its lifeblood and fundamentally opaque.[^McQuillan] This combination means that machine listening is simultaneously an alibi or front for the proliferation and normalisation of specific auditory practices *as* machinic, and, conversely, often irreducible to human apprehension; which is to say the worst of both worlds. -Moreover, because machine listening is so deeply bound up with logics of automation and pre-emption, it is also recursive. It feeds its listenings back into the world - (gendered and gendering),(15.46 - 23.10)[^YS] colonial and colonizing, ![raced and racializing](audio:static/audio/halcyon-siri-imperialism.mp3),[^halcyon_audio_1] classed and productive of class relations - as Siri's answer or failure to answer; by alerting the police, denying your [claim for asylum](https://www.theverge.com/2017/3/17/14956532/germany-refugee-voice-analysis-dialect-speech-software), or continuing to play Autechre - and this incites an auditory response to which it listens in turn. The soundscape is increasingly cybernetic. Confronting machine listening means recognising that common-sense distinctions between human and machine simply fail to hold. We are all machine listeners now. We have been becoming machine listeners for a long time. Indeed, the becoming machinic of listening is a foundational concern for any contemporary politics of listening; not because mechanisation *itself* is a problem, but because it is the condition in which we increasingly find ourselves.[^Abu Hamdan] +Moreover, because machine listening is so deeply bound up with logics of automation and pre-emption, it is also recursive. It feeds its listenings back into the world - ![gendered and gendering](audio:https://machinelistening.exposed/library/Yolande%20Strengers,%20Jenny%20Kennedy,%20Ja/Yolande%20Strengers%20and%20Jenny%20Kennedy%20(10)/Yolande%20Strengers%20and%20Jenny%20Ken%20-%20Yolande%20Strengers,%20Jenny%20Kenned.mp3|946000|1390000),[^YS] colonial and colonizing, ![raced and racializing](audio:static/audio/halcyon-siri-imperialism.mp3),[^halcyon_audio_1] classed and productive of class relations - as Siri's answer or failure to answer; by alerting the police, denying your [claim for asylum](https://www.theverge.com/2017/3/17/14956532/germany-refugee-voice-analysis-dialect-speech-software), or continuing to play Autechre - and this incites an auditory response to which it listens in turn. The soundscape is increasingly cybernetic. Confronting machine listening means recognising that common-sense distinctions between human and machine simply fail to hold. We are all machine listeners now. We have been becoming machine listeners for a long time. Indeed, the becoming machinic of listening is a foundational concern for any contemporary politics of listening; not because mechanisation *itself* is a problem, but because it is the condition in which we increasingly find ourselves.[^Abu Hamdan] But machine listening isn't exactly listening either. @@ -135,4 +135,5 @@ Another response would be to say that when or if machines listen, they listen ![ [^halcyon_audio_1]: Interview with [Halcyon Lawrence](http://www.halcyonlawrence.com/) on August 31, 2020. [^Virilio]: LIBRARY Paul Virilio, *Sightless Vision* [^Faroki, Paglen]: LIBRARY; Mark Andrejevic, [Operational Listening (Eavesdropping)](https://youtu.be/OxOKlgsc3_M), recorded on August 10, 2018 -[^Billy Li]: LIBRARY: Li et al, Adversarial Music: Real world Audio Adversary against Wake-word Detection System (2019). For a good introduction to adversarialism, see LIBRARY Goodfellow \ No newline at end of file +[^Billy Li]: LIBRARY: Li et al, Adversarial Music: Real world Audio Adversary against Wake-word Detection System (2019). For a good introduction to adversarialism, see LIBRARY Goodfellow +[^YS]: ![](bib:26f7b730-9064-464b-b905-fbe63c5d4e4b) \ No newline at end of file diff --git a/data/books/catalog.json b/data/books/catalog.json index db5c38a..142d8b2 100644 --- a/data/books/catalog.json +++ b/data/books/catalog.json @@ -1 +1 @@ -{"6676af8a-7a4d-4aa8-af96-f26452f58753": {"title": "Divination Engines: A media History of Text Prediction", "title_sort": "Divination Engines: A media History of Text Prediction", "pubdate": "2017-06-15 00:00:00+00:00", "last_modified": "2020-06-09 12:00:37.880000+00:00", "library_uuid": "ac02bcce-a920-4add-befb-1dbc71589681", "librarian": "Em Azon", "_id": "6676af8a-7a4d-4aa8-af96-f26452f58753", "tags": ["_tablet_modified"], "abstract": "", "publisher": "", "authors": ["Xiaochang Li"], "formats": [{"format": "pdf", "file_name": "Divination Engines_ A media His - Xiaochang Li.pdf", "dir_path": "Xiaochang Li/Divination Engines_ A media History (2)/", "size": 19319089}], "cover_url": "Xiaochang Li/Divination Engines_ A media History (2)/cover.jpg", "identifiers": [{"scheme": "bibhash", "code": "ARvOPJspR1SF"}], "languages": []}, "f5f0b4ef-9603-4aea-aa40-b5d0fbb9f4d7": {"title": "Smart Home Report", "title_sort": "Smart Home Report", "pubdate": "2018-06-15 00:00:00+00:00", "last_modified": "2020-06-09 12:00:43.520000+00:00", "library_uuid": "ac02bcce-a920-4add-befb-1dbc71589681", "librarian": "Em Azon", "_id": "f5f0b4ef-9603-4aea-aa40-b5d0fbb9f4d7", "tags": [], "abstract": "", "publisher": "", "authors": ["Audio Analytic"], "formats": [{"format": "pdf", "file_name": "Smart Home Report - Audio Analytic.pdf", "dir_path": "Audio Analytic/Smart Home Report (3)/", "size": 2653494}], "cover_url": "Audio Analytic/Smart Home Report (3)/cover.jpg", "identifiers": [{"scheme": "bibhash", "code": "+mTIjocigTCv"}], "languages": []}, "fc275850-d172-4ec1-ab4e-db5c4cc2b5df": {"title": "A Framework for the Robust Evaluation of Sound Event Detection", "title_sort": "A Framework for the Robust Evaluation of Sound Event Detection", "pubdate": "2020-06-15 00:00:00+00:00", "last_modified": "2020-06-09 12:00:47.729000+00:00", "library_uuid": "ac02bcce-a920-4add-befb-1dbc71589681", "librarian": "Em Azon", "_id": "fc275850-d172-4ec1-ab4e-db5c4cc2b5df", "tags": ["electrical engineering and systems science - audio and speech processing", "computer science - sound"], "abstract": "This work de\ufb01nes a new framework for performance evaluation of polyphonic sound event detection (SED) systems, which overcomes the limitations of the conventional collar-based event decisions, event F-scores and event error rates. 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