Origins, structure and evolution of langauge

1. Origins, structure and evolution of langauge

2. What is language? • Communication • Signals emitted by an organism whose function is to influence other organisms (of the same species) • Symbolic • There is little or no relationship between nature and meaning of the signal • Generative • Different combinations of the same signals

3. Do other primates have language? • Vervet monkeys • Warning vocalisations specific to eagle, snake, leopard • Rhesus monkeys • Can distinguish vocalisations such as [p] from [b] (like infants) • Chimpanzees • Wild animals highly vocal • Nim Chimpsky signing patterns (food item first, name at end) • Kanzi (bonobo) word order preferences using pictograms

4. Human-specific language innovations • Physical changes • Lower larynx gives greater range of vocalisations • Nasal cavity can be sealed off giving greater range of vowel sounds • Muscular tongue • Elaboration of brain areas (Left Cortex) • Broca’s area (production) • Wernicke’s area (reception)

5. Language fossils • Artefacts • Genes • Language must be at least as old as the ancestor of modern humans • Genetic similarities between populations reflect linguistic similarities • Possible universal cognates • AQ’WA = water • TIK = finger, one • MAMA, PAPA

6. Linguistic diversity • 5,000+ extant languages; many dialects • 100s of language groups (Indo-European is just one!) • Huge grammatical and phonetic diversity • Immutable/inflective/agglutinating • Fixed/free word order • Subject/topic prominent • SVO/SOV/VSO He is eating for her English Näïkìmlyìïà Kivunjo (Bantu)

7. Semitic Arabic Hebrew Sanskrit Avestan Indo-European Clas. Greek Latin Gothic Old Irish Turkish Turkic Language groups in Europe • Sir William Jones, 1786 • Recognised relationships between different languages pointed to common origin

8. How do languages evolve? • Changes in word use • Nouns become verbs (mail), adjectives change meaning (cool), • Origin/loss of cognates • Hound original term, ‘dog’ appears later • Changes in pronunciation • The great vowel shift (15th C.). E.g. mood previously pronounced ‘mode’, house pronounced with vowel sound of ‘loose’ • Changes in grammar • Loss of gender in English, disuse of ‘thou’, ‘whom’

9. Why do languages evolve? • Cultural exchange • Denim, Tennis, Dandelion, Assassin • Novel situations • Surfing, cookie, blog • Phonetic laziness! • Water pronounced as ‘wadr’ • Identity and slang • Coded meaning (e.g. rhyming slang)

10. Universal Grammars • All individuals have an inbuilt potential to generate grammatical structures • These consist of nouns, verbs, subject-object-indirect object relations, clause structures, etc. • To a large extent this universal grammar (UG) is hard-wired • Wild-children (e.g. Genie) develop protolanguage in absence of stimulus • Genetic basis of specific language impairment • Children’s generalising ability (e.g. wugged) • Differences between languages in phonemes, words and grammatical parameters

11. S VP NP NP det N V det N Language trees The student failed the test

12. Stochastic grammars • We can describe sentences by sets of generative rules

13. Language parameters • Major differences in grammatical structure can be due to small differences in grammatical parameters Baker (2003)

14. Major difference is presence/absence of polysynthesis • If present word order flexible but word structure complex and rigid • E.g. in Mohawk participant must be named in the verb that names the event Rukwe’ wa-sh-ako-hsir-u ne owira’a Man past-he-her-blanket-gave the baby Baker (2003)

15. Why do grammars evolve? • Drift in small populations • Individuals make errors • In small populations errors may be passed between generations • Encryption (Baker, 2003) • Encoding messages so that only a select few can interpret the answer may be important • Letter substitution = Phoneme differences, Transposition = parameter differences • Navajo code talkers of WWII

16. Grammatical structures are an example of stochastic grammars • Generate algorithms for constructing strings • E.g. stochastic context-free grammars (SCFGs) consist of terminal states generated by internal states independent of context E.g Note that there might be many different types of internal state, each of which generates certain sets of terminals and other states. E.g. NP generates terminals (nouns, determiners, adjectives) and other states (PP, NP,…)

17. Stochastic Grammars in Bioinformatics S → LS | L F → dFd | LS L → s | dFd s = unpaired bases d = paired bases S = non-terminal producing loops F = non-terminal producing stems L = non-terminal producing unpaired bases or new stems Knudsen and Hein (1999). Bioinformatics 15:446

18. S S VP VP NP NP PP PP NP NP NP NP V* V* How do we understand language? • For stochastic grammars there is a dynamic programming solution that allows us to consider all possible parsings of a given string N Adv V det N P det N I once shot an elephant in my pyjamas Groucho Marx

19. Is this how humans learn and process? • Th hmn cpcty fr dcdng mprfct sgnls s rmrkbl • We unexpected grammar can even sense make of • Humans … predictive … to … in … gaps • iasudiahsuandcanquicklyspotpatternssdfskkdflgdfkgmfk

20. References • Pinker,S. (1994) The Language Instinct. Penguin • Burchfield, R. (1985) The English Language. OUP • Aitchison, J. (1996) The Seeds of Speech. CUP • Ruhlen, M. (1994) The Origin of Language. Wiley • Crystal, D. (1987). The Cambridge Encyclopedia of Language. CUP • Purves, D. et al (2000). Neuroscience. Sinauer • Baker, M. (2003). Linguistic differences and language design. Trends Cog. Sci. 7:349 • Nowak et al. (2001). Evolution of universal grammar. Science 291:114 • Durbin et al. (1999). Biological Sequence Analysis. CUP