Morphosyntactic annotation of the C-ORAL Brasil Corpus - VISL

Morphosyntactic annotation
of the C-ORAL Brasil Corpus
Eckard Bick
University of Southern Denmark
eckhard.bick@mail.dk

Introduction
● Spoken language corpora are becoming more available, growing in
scope and size
● To fully exploit such corpora linguistically, grammatical annotation is
needed in addition to phonetic-prosodic annotation
● Problems
Speech data are notationally ”colourful” and use different
strategies for retaining non-text information in transcription
Spoken language has many non-standard features, both in
grammar and lexicon

Some comparable projects
● C-ORAL sister projects, using statistical taggers, no syntax
Italian: PiTagger (Moneglia et al. 2004) with lexicon (107.000 standard
lemmas and 2000 non-standard forms) and training corpus (50.000
words ~ 25% of C-ORAL size)
European Portuguese: Brill tagger (Brill 1993) with written Portuguese
training corpus (250.000 words)
● Arabic treebank, i.e. syntax (Maamouri et al. 2010)
manual selection of analyzer suggestion, followed by automatic parsing
not directly comparable: broadcast news, not spontaneous speech
● Our approach: Constraint Grammar annotation
context-driven rules rather than statistics

Why Constraint Grammar
● robust annotation methodology (Karlsson et al. 1994)
focus on disambiguation - no breakdowns due to generative rules
token-based annotation, one tag per feature --> easy to filter
modular methodology --> allows the combination of grammars targeting
different linguistic levels
● existing parser for Portuguese: PALAVRAS (Bick 2000)
has been succesfully used on a large variety of genres (Linguateca
project, CorpusEye)
has proven adaptability in the face of non-standard data, e.g. historical
texts (Bick & Módolo 2005)
keeps annotation levels seperate, while allowing them to interact
– e.g. prosodic versus syntactic information

CG in comparable projects
● Other projects with CG annotation of speech corpora
Estonian speech corpus (Müürisep & Uibo 2006)
Nordic Dialect Corpus (Bondi et al. 2009), hybrid method
– (a) written-language CG used on Oslo dialaect
– (b) manual correction
– (c) train Decision Tree Tagger (Schmid 1994) for other dialects
Spanish section of European C-ORAL
– CG-inspired rules for PoS disambiguation of morphological output
from the GRAMPAL system (Moreno 2003)
Early experiments with PALAVRAS (Bick 1998)
– NURC corpus (”Norma Lingüística Urbana Culta”, Castilho 1993)

The point of departure: PALAVRAS
● Modular Constraint Grammar (CG) parser with a hierarchically
structured sets of contextual rules
morphosyntactic tagging, dependency trees
6000 rules, full lexical support, semantics
O DET M S @>N #1->3
último ADJ M S @>N #2->3
diagnóstico N M S @SUBJ> #3->9
elaborado V PCP2 M S @ICL-N< #4->3
por PRP @4
a DET F S @>N #6->7
Comissão=Nacional PROP F S @P< #7->5
não ADV @ADVL> #8->9
deixa V PR 3S @FMV #9->0
dúvidas N F P @9
$. #11->0

TEXT
Morphology
Analyzer
Cohorts
“”
“crear” V PR 3S IND
“crear” V IMP 2S
“creer” V PR 1/3S SUBJ
sem. roles
...
Lexica
polysemy
Disambiguation
Mapping
Disambiguation
Disambiguation
Mapping
CG flowchart
Syntax
Mapping
PSG
Dep.
External
e.g.DTT
Substitution
external
modules
tagger

Text flow normalisation

Text flow: problems
● nesting and overlapping markers (the latter also
problematic in xml)
● focus marker é_que (2% of turns) transcribed as que ->
need for disambiguation
● syntax needs (separate) prepositions
built-in ordinary contractions: do, nele, pelo ...
corpus-specific: pa (pra), pro, pum, naquea ...
difficult ambiguity: pra (para vs. para_a)
● post-tokenization (coral-inter) with support from
normalization lexicon for the most difficult contractions,
e.g. né = não é

Lexical and orthographical
normalization
● Parser's treatment of unknow wordforms:
Affix derivations
Variants: br vs. pt, accents, orthogr. reform
● Special needs for C-ORAL speech corpus
phonetically transcribed word forms
grammatical variants (-amos -> -amo)
● Solutions: two-level annotation and specialized standardisation modules
meninim OALT menininho [menino] N M S
coral.inter: second preprocessor with systematic and item-based changes
postlex_pt: postprocessor with morphological analyzer using separate lexicon (2000
entries) and overriding PALAVRAS' heuristics

(a1) emedebê MDB (phonetic abbreviations)
(b3) inda ainda ( (word-initial changes)
(b4) roz arroz
(d2) fazido feito (overregularization)
● Multi-word strings: effect also tokenization, but help disambiguate their
parts, e.g.
n' = não (not em) in: n'=era, n'=ocê
● Non-systematic new words and names:
(a1) fazeção N F S
(a2) zenes N M P # termo de jogo
(a3) caça-talentos N M S
(a5) superbem-arrumada ADJ F S
(b) mil-oitocentos-e=vovó=gostosa NUM M/F P
(c1) remote N M S # estrangeirismo
(c2) completed ADJ M/F S/P # estrangeirismo
(c5) anche ADV # estrangeirismo
(d1) tu=tu X # onomatopéia
(e2) TIM PROP F S # company
(e3) Timoftol PROP M S

unknown / nonstandard
input
coral.pre
tokenization
PALAVRAS preprocessor
e.g. complex prp, names
coral.inter
normalization
PALAVRAS analyzer
heuristics
postlex_pt
analysis of
”unknown” words
CG disambiguation
● Add-on lexicon used to add
readings rather than override
the parsers, allowing for
contextual disambiguation, even
of unintended ambiguity:
pô --> pôs ---> verb vs.
interjection plural (allowed in C-
ORAL)
CG syntax
pt_forms
_coral
newlex_pt
dependency

Syntax
● Problem: syntactic noise: ah, eeh, uh
Solution: two-level annotation
● Problem:Syntactic annotation needs long-distance contexts, so how can existing rules
be made to work on a speech corpus
> 80% unbounded/global CG rules in syntax
but the corpus lacks sentence segmentation and punctuation to delimit these rules
Solution: Exploit prosodic information by not moving it to a meta-level, but rather
change it into punctuation
● // (major prosodic break) --> semicolon
● / (soft prosodic break) -->

prosodic ”break markers”:
rule-based disambiguation
● --> comma
● --> meta-level
(a) between a noun or a nominative pronoun or a conjunction to the
left, and a finite verb to the right, a prosodic /-marker is treated
as (subject - verb case)
(b) prosodic /-markers between a noun and another np are treated
as (appositions)
(c) / between a prenominal and its head is treated as (np
cohesion), e.g. 388 cases of article +
... tipo Zé=Mourinho falando
assim não
o [o] DET M S @>N
[campeonato] N M S @SUBJ>
d' OALT de [de] PRP @N<
ocês OALT vocês [você] PERS M/F 3P NOM/PIV @P<
é [ser] V PR 3S IND VFIN @FMV

Evaluation
● random transcription file (1895 tokens)
● eval_cg tool raw analysis file and revised version
● challenge: alignment in the face of punctuation ambiguity

Effectiveness of using prosodic break
markers as punctuation
● standard run: pause/break disambiguation
● no-break: /-marks ignored
● no-sentence: both /- and //-marks ignored
● all-break: all /-marks as commas, no disambiguation

using prosodic breaks for syntax:
results
● prosodic break markers do help the parser
● more so for syntax than PoS/morphology (wider contextual
scope with corresponding segmentation needs)
● pause/break disambiguation more relevant for syntax than PoS

graphical search interface

concordances

statistics

contrastive searches: N dela - N dele

comparative search across corpora

cqp speak: [pos="ADJ" & func="N

Conclusions
● A standard written-language parser (PALAVRAS) can be used to
assign morphosyntactic tags to transcribed speech data
● For optimal performans, certain adaptations are necessary:
orthographical normalization
lexicon extensions
syntactic segmentation (disambiguation of prosodic breaks)
● Under optimal conditions, almost-normal F-scores can be
achieved (98.6% PoS, 95% syntax, 99% lemmatization)

Outlook
● Annotation scheme does preserve the original prosodictranscriptional
information (speech flow, retractions, overlaps
etc.) encoded as metatagging alongside morphosyntactic tags,
but how to make this accessible to GUI searches
searchable now on with grammar: prosodic breaks
not searchable now: speech flow, retractions, overlaps
● Wish lish: higher level annotation:
Dependency (done)
semantic classes and roles
anaphoric relations ....

References 1
Bick, Eckhard. 2000. The Parsing System Palavras - Automatic Grammatical Analysis of
Portuguese in a Constraint Grammar Framework, Aarhus: Aarhus University Press
Bick, Eckhard. 1998. Tagging Speech Data - Constraint Grammar Analysis of Spoken
Portuguese, in: Proceedings of the 17th Scandinavian Conference of Linguistics (Odense
1998)
Bick, Eckhard & Marcelo Módolo. 2005. Letters and Editorials: A grammatically
annotated corpus of 19th century Brazilian Portuguese. In: Claus Pusch & Johannes
Kabatek & Wolfgang Raible (eds.) Romance Corpus Linguistics II: Corpora and Historical
Linguistics (Proceedings of the 2nd Freiburg Workshop on Romance Corpus stics, Sept.
2003). pp. 271-280. Tübingen: Gunther Narr Verlag.
Brill, Eric. 1992. A simple rule-based part of speech tagger. In: Proceedings of the
workshop on Speech and Natural Language. HLT '91, Morristown, NJ, USA: Association
for Computational Linguistics, pp.112–116
Castilho, Ataliba de (ed.), 1993. Gramática do Português Falado, vol.3, Campinas:
Editora da Unicamp.
Johannessen, Janne Bondi, Joel Priestley, Kristin Hagen, Tor Anders Åfarli, and Øystein
Alexander Vangsnes. 2009. The Nordic Dialect Corpus - an Advanced Research Tool. In
Jokinen, Kristiina and Eckhard Bick (eds.): Proceedings of the 17th Nordic Conference of
Computational Linguistics NODALIDA 2009. NEALT Proceedings Series Volume 4
Karlsson, Fred & Voutilainen, Atro & Heikkilä, Juka & Anttila, Arto. 1995. Constraint
Grammar, A Language-Independent System for Parsing Unrestricted Text. Berlin: Mouton
de Gruyter.

References 2
Maamouri, Mohamed et al. 2010. From Speech to Trees: Applying Treebank Annotation
to Arabic Broadcast News. In: Proceedings of LREC 2010, Valletta, Malta, May 2010.
Moreno, A. & J.M. Guirão. 2003. "Tagging a spontaneous speech corpus of Spanish". In:
Proceedings of the International Conference on Recent Advances in Natural Language
Processing.). Borovets, Bulgaria, 2003. p. 292-296.
Müürisep, Kaili and Uibo, Heli (2006). "Shallow Parsing of Spoken Estonian Using
Constraint Grammar". In: P.J.Henriksen & P.R.Skadhauge, Proceedings of NODALIDA-
2005 special session on treebanking. Copenhagen Studies in Language #33/2006
Moneglia, M., A. Panunzi, E. Picchi, 2004, Using PiTagger for Lemmatization and PoS
Tagging of a Spontaneous Speech Corpus : C-Oral-Rom Italian. In M.T. Lino et al. (eds.),
Proceedings of the 4th LREC Conference, vol. 2, ELRA, Paris, pp. 563-566.
Raso, Tommaso & Heliana Mello. 2010. The C-ORAL BRASIL corpus. In: Massimo
Moneglia & Alessandro Panunzi (eds): Bootstrapping Infromation from Corpora in a
Cross-Linguistic Perspective. Universitá degli studi di Firenze, Biblioteca Digitale.
Schmid, Helmut. 1994. Probabilistic Part-of-Speech Tagging Using Decision Trees.
Proceedings of the International Conference on New Methods in Language Processing
1994. pp. 44-49.

visl.sdu.dk (parsers)
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