Different languages, similar encoding efficiency: Comparable information rates across the human communicative niche

Coupé, Christophe; Oh, Yoon Mi; Dediu, Dan; Pellegrino, François

doi:10.1126/sciadv.aaw2594

Cited by 143 publications

(131 citation statements)

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“…To the extent that this is interpreted as being a compensatory relation, this would indicate that word length is being taken as an implicit measure of complexity. Alternatively, word length has a natural interpretation in terms of information rate, so trade-offs could be attributed to communicative capacity (Pellegrino et al, 2011;Coupé et al, 2019).…”

Section: Measures Of Phonological Complexitymentioning

confidence: 99%

“…Such compensation has been hypothesized to be the result of natural processes of historical change, and is sometimes attributed to a potential linguistic universal of equal Cross Entropy (bits per phoneme) Figure 1: Bits-per-phoneme vs average word length using an LSTM language model. communicative capacity (Pellegrino et al, 2011;Coupé et al, 2019). Methods for making hypotheses about linguistic complexity objectively measurable and testable have long been of interest, though existing measures are typically relatively coarse-see, e.g., Moran and Blasi (2014) and §2 below for reviews.…”

Section: Introductionmentioning

confidence: 99%

“…See alsoCoupé et al (2019), where syllable-based bigram models are used to establish a comparable information rate in speech across 17 typologically diverse languages.…”

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confidence: 99%

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Phonotactic Complexity and Its Trade-offs

Pimentel

Roark

Cotterell

2020

Transactions of the Association for Computational Linguistics

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We present methods for calculating a measure of phonotactic complexity-bits per phoneme-that permits a straightforward cross-linguistic comparison. When given a word, represented as a sequence of phonemic segments such as symbols in the international phonetic alphabet, and a statistical model trained on a sample of word types from the language, we can approximately measure bits per phoneme using the negative log-probability of that word under the model. This simple measure allows us to compare the entropy across languages, giving insight into how complex a language's phonotactics are. Using a collection of 1016 basic concept words across 106 languages, we demonstrate a very strong negative correlation of −0.74 between bits per phoneme and the average length of words.

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Section: Measures Of Phonological Complexitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Phonotactic Complexity and Its Trade-offs

Pimentel

Roark

Cotterell

2020

Transactions of the Association for Computational Linguistics

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“…While conscious experience may be "flat" (Chater, 2018), in terms of being of surprisingly low dimensionality, IWMT argues that the functioning of consciousness within an overall mental system may also be deep. This point about the multiply-determined contextual significances of reduced-dimensional processing may be well-expressed in terms of recent findings that nearly all languages may converge on a common information transmission rate of ~39 bits/second (Coupé et al, 2019). Indeed, the low dimensionality of conscious processing may be the primary reason for this communicative bottleneck.…”

Section: Richness Of Consciousness and Grand Illusionsmentioning

confidence: 87%

Integrated World Modeling Theory (IWMT) Revisited

Safron¹

2019

Preprint

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Here, I provide clarifications and discuss further issues relating to Safron (2020), “An Integrated World Modeling Theory (IWMT) of consciousness: Combining Integrated Information and Global Workspace Theories with the Free Energy Principle and Active Inference Framework; towards solving the Hard problem and characterizing agentic causation.” As a synthesis of major theories of complex systems and consciousness, with IWMT we may be able to address some of the most difficult problems in the sciences. This is a claim deserving of close scrutiny and much skepticism. What would it take to solve the Hard problem? One could answer the question of how it is possible that something like subjectivity could emerge from objective brain functioning (i.e., moving from a third person to a first person ontology), but a truly satisfying account might still require solving all the “easy” and “real” problems of consciousness. In this way, IWMT does not claim to definitively solve the Hard problem, as explaining all the particular ways that things feel across all relevant aspects of experience is likely an impossible task. Nonetheless, IWMT does claim to have made major inroads into our understanding of consciousness, and here I will attempt to justify this position by discussing challenging problems and outstanding questions with respect to philosophy, (neuro)phenomenology, computational principles, practical applications, and implications for existing theories of mind and life.

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“…For example, the coding of the 207 meaning of conspecific vocalizations in different brain areas 23,41,43,45 . In conclusion, the 208 behavioural paradigm we present could advance the study of acoustic recognition at the 209 neuronal level, because, in contrast to humans 46 , trained monkeys present only a few dozen The acoustic recognition task (ART) consisted of identifying T and N sounds. Fig.…”

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confidence: 98%

Perceptual Invariance of Words and Other Learned Sounds in Non-human Primates

Melchor

Morán

Figueroa

et al. 2019

Preprint

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Our ability to invariably identify words spoken with different accents and timbres requires 1 our perception to tolerate multiple acoustic modulations. However, the mechanisms by 2 which lexical information is perceived to be invariant is unknown. In this study, we 3 explored the ability of two trained rhesus monkeys to recognise many sounds, including 4 multisyllabic words presented in numerous variations. We found that the monkeys' lexical 5 representations are remarkably tolerant of dynamic acoustic changes. Furthermore, we 6 determined that the macaques invariably recognise sounds with formants at close Euclidean 7 distances from a learned category. Based on our results, we propose the possible existence 8 of neuronal circuits responsible for the invariant recognition of lexical representations in 9 macaques. 10 11 14 vital for communication in primates, the perceptual basis of invariant recognition of sounds 15has not extensively investigated. One possible reason for this is that non-human primates 16 may only demonstrate limited acoustic learning 4-6 , and that therefore their recognition 17 capability may depend on genetically-programmed circuits 7-9 . However, it is known that 18 macaques are capable of learning repertoires of visual categories 10 and even declare the 19 existence of objects with ambiguous or incomplete information 11 . Studies of the 20 inferotemporal and prefrontal cortices of monkeys showed neurons whose categorical 21 responses achieved the grouping of wide variations of images [12][13][14] , which is consistent with 22 perceptual reports 15,16 . Similarly, experiments in the prefrontal cortex and secondary 23 3 acoustic areas suggest invariant coding of acoustic categories [17][18][19][20][21][22][23][24][25] . In this paper, we sought 24 to determine what acoustic parameters stand for the invariant recognition of sounds (IRS) 25 in trained non-human primates 26 . We hypothesised that monkeys invariably recognise 26 sounds of frequency-saliences with dynamics similar to sounds the monkeys had 27 learned 27,28 . To test this, we designed a novel paradigm in which the macaques efficiently 28 reported target (T) sounds presented in sequences that included nontarget (N) sounds. We 29 found that the monkeys recognised sound fragments of frequency modulations in the range 30 of the prominences of the learned sounds as invariants. Our results allowed us to elucidate, 31 for the first time, the acoustic parameters 29-34 that lead to monkeys' IRS. We propose that 32 the ability to group complex stimuli into particular categories is served by chunks of 33 prominent features of the stimuli. 34 35 Results 36We trained two rhesus monkeys in an acoustic recognition task in order to study the 37 invariant recognition of sounds. During the task, the monkeys obtained a reward for 38 releasing a lever after identifying a T presented after zero, one or two Ns ( Fig. 1a-c; see 39 Methods). After two years of training, monkey V recognised seven Ts and twenty-one Ns, 40 and monkey X recognised eleven Ts a...

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Different languages, similar encoding efficiency: Comparable information rates across the human communicative niche

Cited by 143 publications

References 55 publications

Phonotactic Complexity and Its Trade-offs

Phonotactic Complexity and Its Trade-offs

Integrated World Modeling Theory (IWMT) Revisited

Perceptual Invariance of Words and Other Learned Sounds in Non-human Primates

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