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Partial Reduplication Single Morphological Categories and Their Frequencies Sōu~ Sōu BB 29.6% ‘Sound of Wind’ RR 25.3% Yǎn~Yàng ‘Waves Crashing’

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Partial Reduplication Single Morphological Categories and Their Frequencies �� Sōu~ Sōu BB 29.6% ‘Sound of Wind’ RR 25.3% �� Yǎn~Yàng ‘Waves Crashing’ Bridging phonology, meaning, and written form across time: Introducing a database of Chinese ideophones — CHIDEOD Thomas Van Hoey National Taiwan University ILL-12 12th International Symposium on Arthur L. Thompson Iconicity in Language and Literature The University of Hong Kong 3-5 May 2019, University of Lund Ideophones: a typologically widespread phenomenon Dingemanse’s definition marked words that depict sensory imagery (2011; 2012) [and that belong to an open lexical class] (2019) 2 What we know about Chinese ideophones Some cross-linguistically notable features of ideophones (cf. a.o. Dingemanse & Akita 2016) • prosodic foregrounding • often less integrated in sentences • often marked by reduplication • expands on the phonological system of prosaic words • gesture • variable written forms What we know about Chinese ideophones Some cross-linguistically notable features of ideophones (cf. a.o. Dingemanse & Akita 2016) • prosodic foregrounding • often less integrated in sentence • often marked by reduplication • expands on the phonological system of prosaic words • gesture • variable written forms (1) tā xiū=de=yì-shēng pǎo-guò-qù=le she IDEO=ADV one-sound run-past-go=PFV “Shoow, she ran by.” (2) fēijī xiū xiū xiū fēi-guò-qù airplane IDEO IDEO IDEO fly-over-go. The planes whizzed over. What we know about Chinese ideophones Some cross-linguistically notable features of ideophones (cf. a.o. Dingemanse & Akita 2016) • prosodic foregrounding • often less integrated in sentence • often marked by reduplication • expands on the phonological system of prosaic words • gesture • variable written forms (1) tā xiū=de=yì-shēng pǎo-guò-qù=le she IDEO=ADV one-sound run-past-go=PFV “Shoow, she ran by.” Actor Jackie Chan performing newly coined ideophone duāng ‘very black, thick and smooth hair’ > ‘wow!’ (2) fēijī xiū xiū xiū fēi-guò-qù airplane IDEO IDEO IDEO fly-over-go. Cheng Long ‘Jackie Chan’ The planes whizzed over. 5 What we know about Chinese ideophones Chinese research on Chinese ideophones is mostly concentrated Zhao Aiwu (2008) on onomatopoeia (ideophones that depict sound). Qiu Di (2018) 6 What we know about Chinese ideophones Chinese research on Chinese ideophones is mostly concentrated Zhao Aiwu (2008) on onomatopoeia (ideophones that depict sound). Qiu Di (2018) However, there are some broader discussions of ideophones • phonology Mok (2001); Thompson (2018) • Beijing dialect Meng (2012) • Southern Sinitic Wu (2014) • Cantonese (vs. Dagaare) Bodomo (2006) • Mandarin (vs. Japanese) You (2015) • Japanese (vs. Mandarin) Lu (2006) • reduplication in Old Chinese Sun (1999) • Middle Chinese Van Hoey (2015) 7 What we know about Chinese ideophones Chinese research on Chinese ideophones is mostly concentrated Zhao Aiwu (2008) on onomatopoeia (ideophones that depict sound). Qiu Di (2018) However, there are some broader discussions of ideophones • phonology Mok (2001); Thompson (2018) • Beijing dialect Meng (2012) • Southern Sinitic Wu (2014) • Cantonese (vs. Dagaare) Bodomo (2006) • Mandarin (vs. Japanese) You (2015) • Japanese (vs. Mandarin) Lu (2006) • reduplication in Old Chinese Sun (1999) • Middle Chinese Van Hoey (2015) These studies often append data to their work (good!) but the data is not standardized so not always reusable (less good). 8 How can we unify what we know about Chinese ideophones? We need to centralize these data so they can be reused • Dedicated studies • Dictionaries • (scattered examples) Our answer: CHIDEOD — the Chinese Ideophone Database Collecting data from these sources, storing them in a user-friendly dataset and repository, provide a number of formal and semantic variables that can be explored 9 Similar databases: BCCWJ’s word profiler Balanced Corpus of Contemporary Written Japanese (NINJAL 2016) has a word profiler (LWP) The word profiler looks up words in the BCCWJ and provides sketch grammar-like statistics. The goal of CHIDEOD is to collect all TYPES, all noun verb adj. conj. adv. mimetic which later could be used in a corpus study 10 Similar databases: MEJaM The Multimedia Encylcopedia of Japanese Mimetics (Akita 2016) bururu [collocation] verb adjective nouns CHIDEOD might eventually evolve into a Multimedia CHIDEOD Which would include pictures and video clips to illustrate the depictive nature. However, given the diachronic and synchronic scope, this may not be realizable for all items. buru~buru 11 Similar databases: Quechua Real Words Audiovisual ANTI-dictionary of expressive Quechua ideophones (Nuckolls 2017; Nuckolls & Swanson 2019) The goal is to study the multimodal interaction between Quechua ideophones and gesture through video clips Subsets of data provided in CHIDEOD can aid in researching how multimodality(gesture) interacts with Chinese ideophones. polan 12 CHIDEOD: why and where • digitization of data Open source project available at OSF • centralization of data https://osf.io/kpwgf/ • exploration • semantics Available as online app • phonology https://simazhi.shinyapps.io/Chineseide • ortography ophone/ • historical • expandable research resource Also available as an R package rather than the finalized tool (see osf website) • type frequencies (not yet token frequencies) 13 CHIDEOD is structured in a tidy format • Ever growing resource • Modeled after the recent Chinese Lexical Database Sun et al. (2018) • Lives mostly as a large tidy dataframe 1 character: 3,913 2 characters: 34,233 • R (but also other programming languages like python) 3 characters: 7,143 • Export to csv, excel, pdf 4 characters: 3,355 Total: 48,644 (>200 variables) Wickham (2014); Wickham & Grolemund (2016); Forkel et al. (2018) 14 CHIDEOD (the online app version) 4662 entries; 3452 distinct onomatopoeia and ideophones 15 Variables coded in CHIDEOD 16 35.1% 18.0% 17.9% 14.7% 10.4% 3.9% Sources for CHIDEOD 35.1% 18.0% 17.9% 14.7% 10.4% 3.9% 0 1000 2000 3000 4000 Total number of types Gong (1991) Mandarin Li (2007) Wang (1987) Tang Wang Li datasource Shijing Gong Kroll Van Hoey (2015) Premodern Chinese Kroll (2015) Van Hoey (2016) Dictionaries Dedicated studies 17 0 1000 2000 3000 4000 Total number of types Tang Wang Li datasource Shijing Gong Kroll Formal variables Semantic variables Other variables pinyintone, Kroll dictionary variants pinyinnum, Handian (zdic) pinyinnone phonology word Hanyu Da Cidian note level Middle Chinese (MC) sensory modality datasource Old Chinese (OC) traditional simplified T1-T4 variables S1-S4 morphology character in CHIDEOD S1-S4.charfreq level S1-S4.famfreq orthography S1-S4.sem Abbreviations: S1-S4.semfreq S = simplified, S1-S4.semfam radical support below- T = traditional, character sem = semantic radical, S1-S4.phon level phon = phonetic radical, S1-S4.phonfreq freq = (token) frequency, fam = (type) family frequency S1-S4.phonfam 18 Formal variables Semantic variables Other variables pinyintone, Kroll dictionary variants pinyinnum, Handian (zdic) pinyinnone phonology word Hanyu Da Cidian note level Middle Chinese (MC) sensory modality datasource Old Chinese (OC) traditional simplified T1-T4 variables S1-S4 morphology character in CHIDEOD S1-S4.charfreq level S1-S4.famfreq orthography S1-S4.sem Abbreviations: S1-S4.semfreq S = simplified, S1-S4.semfam radical support below- T = traditional, character sem = semantic radical, S1-S4.phon level phon = phonetic radical, S1-S4.phonfreq freq = (token) frequency, fam = (type) family frequency S1-S4.phonfam 19 Formal variables Semantic variables Other variables pinyintone, Kroll dictionary variants pinyinnum, Handian (zdic) pinyinnone phonology word Hanyu Da Cidian note level Middle Chinese (MC) sensory modality datasource Old Chinese (OC) traditional simplified T1-T4 variables S1-S4 morphology character in CHIDEOD S1-S4.charfreq level S1-S4.famfreq orthography S1-S4.sem Abbreviations: S1-S4.semfreq S = simplified, S1-S4.semfam radical support below- T = traditional, character sem = semantic radical, S1-S4.phon level phon = phonetic radical, S1-S4.phonfreq freq = (token) frequency, fam = (type) family frequency S1-S4.phonfam 20 Formal variables Traditional character Simplified character onomatopoeia ‘cry of an osprey’ 21 Formal variables word level Phonology Traditional guān~guān character guan1~guan1 Simplified guan~guan character Middle Chinese kwaen~kwaen onomatopoeia Old Chinese ‘cry of an osprey’ *[k]ˤro[n]~[k]ˤro[n] (Baxter & Sagart 2014; 2015) 22 Formal variables word level character level Phonology T1 T2 T3 T4 Traditional guān~guān character NA NA guan1~guan1 S1 S2 S3 S4 Simplified guan~guan character NA NA Middle Chinese Character frequency per million kwaen~kwaen 976,716 onomatopoeia Old Chinese Family frequency ‘cry of an osprey’ *[k]ˤro[n]~[k]ˤro[n] 90 (Baxter & Sagart 2014; 2015) 23 Number of syllables in CHIDEOD 2500 Morphology: Number of syllables 2000 1500 1000 number of distinct items distinct of number 500 n = 2 n = 1 0 12345624 number of syllables Based on identifying a • BASE • REDUPLICANT • extra elements (cf. Sun 1999) BASE REDUPLICANT • Mandarin + Middle Chinese • often liquid (or MC reflex) or when base unclear • higher “family frequency” • lower “family frequency” (Sun et al. 2018) Morphology 25 Morphological categories and their frequencies BB 29.6% RR 25.3% RRRR 15.7% BR 9.2% A 7.1% Based on identifying a ARR 4.9% • BASE RB 2.8% • REDUPLICANT BBB 1.9% • extra elements (cf. Sun 1999) RAN 1.6% RRR 0.6% BASE REDUPLICANT RRA 0.6% • Mandarin + Middle Chinese • often liquid (or MC reflex) BBBB 0.4% or when base unclear YAN 0.1% • higher “family frequency” • lower “family frequency”
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