Слайд 1 - Institute of Linguistics, Russian Academy

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Transcript Слайд 1 - Institute of Linguistics, Russian Academy

Andrej A. Kibrik
Olga B. Markus
Local discourse structure
in Upper Kuskokwim Athabaskan
SSILA Conference
Berkeley, July 2009
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Basic information about Upper
Kuskokwim Athabaskan (UKA)
 About 30 speakers left out of the population of
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about 200
Most speakers reside in the village of Nikolai
Actual use of UKA – in two or three households
Prior work – Collins and Petruska 1979
Kibrik’s field trips in 1997 and 2001
As in other Athabaskan:
 polysynthesis
 highly complex verb morphology and morphophonemics
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Data
 Natural discourse recordings (transcribed)
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Folk stories
Personal stories
Conversation (pre-arranged)
Interview at school
 In all – 3 hours 20 minutes of talk
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Lena Petruska, the oldest speaker
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Theory
 Local discourse structure:
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Elementary discourse units (EDUs)
EDUs are elementary behavioral acts of
discourse processing
EDUs are identified on the basis of a cluster of
prosodic features:
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Tonal contour
Central accent
Tempo pattern
Loudness pattern
Pausing
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Example (1): tonal contours
a
b
c
d
e
f
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Example (1b): tempo pattern
a
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b
c
d
sighwdlaɁ 720ms / 3 = 240 ms per syllable
todoltsitł’ ts'eɁ 1800 ms / 4 = 450 ms per syllable
e
f
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Example (1): pausing
a
b
c
d
e
f
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Properties of EDUs
 Prosodically identified EDUs display
interesting content-related properties
 Cognitively: manifest a focus of
consciousness (Chafe)
 Semantically: typically report event/state
 Grammatically: often coincide with clauses
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EDUs and clauses
 Clausal EDUs
 Short EDUs (less than one canonical
clause)
 Long EDUs (more than one canonical
clause)
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EDU types in example (1)
 Clausal: b, c, f
 Short:
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d
e
regulatory (discourse marker)
subclausal (topic)
fragmentary (false start)
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Quantitative data:
an overview
 965 EDUs in the data set
 Clausal EDUs – 70.8%
 Short EDUs – 14.8%
 Long EDUs – 14.4%
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Clausal EDUs (683 = 100%)
 Headed by a lexical verb – 84%
 Headed by a verb of being – 6%
 Non-verbal – 10%
(1b, c)
(1f)
(2)
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Non-verbal clausal EDU
(2) ‘(There was) also lots of marten skins’
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Short EDUs (143 = 100%)
 Regulatory – 13%
 Fragmentary – 20%
 Nominalized – 7%
 Subclausal – 50%
(1a)
(1e)
 Prospective – 42%
 Retrospective – 18%
(1d)
(3)
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Retrospective subclausal
EDUs
Increment:
(3) ‘That is why that happened to me then,
because of the icon’
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Long EDUs (139 = 100%)
 Concatenation – 19%
 Adverbial – 0%
 Relative clause + main clause – 2%
 Non-quotative complement clause
+ main clause – 42%
 Quotative clause + main clause – 37%
(4)
(5)
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Concatenation
(4) ‘He went inside and lay down’
 danaɁediyo
 naztanh
150 ms
385 ms
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Quotative clause +
main clause
(5) ‘You should also come slide with me, I
told her’
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EDUs and clauses in a
typological perspective
Language
English (Chafe 1994)
Percentage
of clausal EDUs
60%
Mandarin (Iwasaki and Tao 1993)
39.8%
Sasak (Wouk 2008)
51.7%
Japanese (Matsumoto 2000)
68%
Russian (Kibrik and Podlesskaya 2009)
68.6%
Upper Kuskokwim
70.8%
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A possible explanation
 Percentage of clausal EDUs is correlated
with the degree of a language’s:
 degree of morphological complexity
 grammatically marked distinction of inflected
verbs from other predicate types
 Probably the languages overtly marking
verbs as dedicated predicative elements
more strongly correlate clauses with EDUs
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Conclusions
 EDUs as universal building blocks of local
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discourse structure are perfectly well identifiable
in a polysynthetic language
EDUs display a high correlation with clauses
Short and long EDU types, as known in other
languages, are also found in Upper Kuskokwim
An account of EDUs and their types is a
necessary component of a grammatical
description of any language, less studied and
endangered languages not excluded
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Some directions for further
research
 Different intonation contours – their
discourse semantics
 Interaction of discourse prosody with
lexical tone, vestigially present in some
idiolects
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TsenɁan!
 Thanks to all speakers of Upper Kuskokwim, both
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mentioned and unmentioned above
Thanks to many individuals and organizations that
helped to collect and process the data, in
chronological order:
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Michael Krauss
James Kari
Raymond Collins
Alaska Native Language Center
Fulbright Program
Endangered Language Fund
Bernard Comrie
MPI for Evolutionary Anthropology, Leipzig
Russian Foundation for the Humanities
National Science Foundation
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Welcome to Nikolai
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