Open Curriculum

Our devices are listening to us. Previous generations of audio-technology transmitted, recorded or manipulated sound. Today our digital voice assistants, smart speakers, and a growing range of related technologies are increasingly able to analyse and respond to it as well. Scientists and engineers increasingly refer to this as “machine listening”, though the first widespread use of the term was in computer music. Machine listening is much more than just a new scientific discipline or vein of technical innovation however. It is also an emergent field of knowledge-power, of data extraction and colonialism, of capital accumulation, automation and control. It demands critical and artistic attention.

This is an open curriculum for machine listening’s study.

Section 0 (’metacurriculum’) is about what the curriculum is, how it is structured, what is meant by openness, and what you might need to know to use or contribute to the curriculum.

Everything from Section 1 on is the curriculum itself, which grows additively and serially. In other words, it gets longer and longer. Rather than edit, rewrite, or delete entries, new additions build on, reframe, intervene in, or comment on existing ones.

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Metacurriculum

0

structuremethods
What is this curriculum?

0a

This curriculum’s history

0a1

Zettelkasten as a structural idea

0a2

methodsexperiments
What is ‘open’ about this open curriculum?

0a2a

How can this curriculum be decolonized, pluralised, or remapped?

0a3

methods
Conscious thinking and continuous education

0a3a

Plurality as transformative, not additive

0a3b

Positionality and site specificity

0a3c

Situating theory

0a3d

Who is this curriculum being written by?

0b

Who is this curriculum for? And how can it be used?

0c

What kind of contributions can you make? And where do they go?

0d

What do the tags mean?

0f

How should I format my contribution?

0g

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Machine listening

1

Forensic listening

1b

truthmethods
Hungry listening

1c

methods
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Techniques of machine listening

2

Audio Fingerprinting

2a

readingtechniques
Shazam as a verb

2a1

methods
Google Content ID

2a2

techniques
Adversarial Audio

2b

techniques
Keyword spotting

2c

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Speech recognition

3

big topic
Histories of speech recognition

3a

Language and speech recognition

3b

What do wake words do?

3c

experiments
Metaphors of machine listening

3d

Metaphors of Alexa Skills Kit

3e

objectsreading
Critical readings of "voice industry" consumer adoption reports

3f

objectsreading
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Voice analysis

5

Accent bias

5a

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Music Information Retrieval

6

Automatic music transcription

6a

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Computational Auditory Scene Analysis (CASA)

7

reading
Calling in Our Corals (Google)

7b

objects
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Datasets

8

big topic
AudioSet

8a

objectsreading
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Instruments

9

Voyager

9a

objects
Word Processor/Decomposer

9b

objects
LANDR

9c

objects
Holly+

9d

objects
The assistive pretext

10

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Surveillance

11

big topic
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Voice Assistants

12

objects
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Audio Deepfakes

13

truthobjects
Voice clone survey

13a

objectsexperiments
Deepfakes beyond deceit

13b

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Labour in/and Machine Listening

14

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Speech Synthesis

15

big topic
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Music

16

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Platforms

17

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Environments

18