design of a multimedia corpus of austronesian linguisticsciet/form/paper/4.doc · web view 3.2...

Design of a Multimedia Corpus of Austronesian Linguistics

Zhemin Lin, Li-May Sung, I-wen Su

Graduate Institute of Linguistics of the National Taiwan University

Abstract In this paper, the design of an integrated platform of multimedia on-

line corpora aiming to serve both linguists and the public is introduced along

with database schema and programming details. Compared with the Formosan

language archive of Academia Sinica, our design emphasizes more in terms of

normalization, accessibility and interoperability of the system. The design of

an automatically generated dictionary with cross-references and the capability

of searching the entire database in various ways are also described here.

1 Introduction

The development of natural language processing techniques and dynamic web pages

has generated wide interest in the construction of an integrated platform which en-

ables people to submit, to browse and to search among collected texts in corpora.

However, most online corpora are specially built for experts; they are sentence-based

and do not provide multimedia contents. The NTU corpus of Austronesian lan-

guages1 introduced in this paper is an attempt to construct a multi-lingual online cor-

pus with multimedia contents meeting the needs of both linguists and the public. In

the following sections, we will take a brief review of previous works and then focus

on the features of our current work.

1 http://corpus.linguistics.ntu.edu.tw

106 Zhemin Lin, Li-May Sung, I-wen Su

2 Formosan Language Archive of Academia Sinica

Zeitoun et al. (2003) discussed some of the problems in the conservation of Formosan

Austronesian languages. The continuous enhancement of their work with many

newly designed tools is further described in Zeitoun and Yu (2005). As discussed in

the two articles, fieldwork data are rarely shared in the linguistic community.

Collected materials are sometimes inaccessible even in the office where they are

stored, due to the change of storage media or data damage. One of the most serious

problems is that, although there are elicitated sentences and recordings, few of them

are rearranged and published. As a response to the problems, researchers in the

Academia Sinica have built a Formosan language archive, i.e., an online corpora with

texts, translations, word glosses and sounds from native speakers of 14 languages and

dialects.2

Despite their labour, there are however insufficiencies in their system, one of

them being the theoretical issue: the Sinica corpora are sentence-based, where pauses,

pause fillers, repetitions, intonation contours, IU boundaries and other discoursal

clues are either discarded or missing. A sentence-based corpus excludes important

linguistic information only present in discourse. Words in the system are written in

an ad hoc mixture style via International Phonetic Alphabet (IPA), in a transcription

style that prevents their respective native speakers from using the data directly.

Nearly every word is altered to some extent. Example (1) is a Saisiyat example

extracted from the Sinica archive.

(1)

(a) yao noka maʔiiæh ... hayðaʔ ʔæhæʔ maʔiiæh la m-waaiʔ, yao mina-

ŋaʔŋaʔ nak hini mina-ʃaaəŋ.

(b) ʔinʔalay hikor may nak hini yakin, ʃβət yakin ho.

(c) ʔok-ik ʃəβət, m-waaiʔ nak hini pa-paʃœʃ, yao h<œm>ʃœʃ atomalan.

(Extracted from 05.002a -- 05.002c of “5.我的故事” of the Sinica archive.)

There is so far no dictionary available with cross-referencing function in the

2 http://formosan.sinica.edu.tw/formosan/ch/select_corpus.htm

Design of a Multimedia Corpus of Austronesian Linguistics 107

Sinica corpus, even though cross-referencing for an online corpus is essential for

researchers deal with elicited or authentic data. Like KWIC (Keyword-in-context, cf.

Luhn (1960)), a user can trace a word back to the context where it occurs, and browse

its surrounding IUs. Zeitoun et al (2003) has planed a data schema that ran on

Microsoft Access. Their design, however, cannot take advantage of the SQL92 query

language. Moreover, they designed an XML dialect to improve the interoperability,

which does not encourage researchers to share their collected data in a convenient

way. The Sinica archive, though primitive in design, is the first attempt to provide

public access to the nearly extinct linguistic data, which is an effort highly respectable

by itself.

3 NTU Corpus of Austronesian Languages

The system designed in this paper is based on the NTU corpus of Austronesian

languages. The NTU corpus, first described in Huang, Su, and Sung (2003), is

composed of spoken texts in various languages. Currently NTU Saisiyat corpus

contains 22 texts, 3081 intonation units (IUs) and approximately 10635 words, whose

transcription follows the conventions of Du Bois (1993). There are one conversation,

eight narratives of indigenous legends, thirteen elicited narratives based on “Pear

Stories” (5 narratives based on a six-minute color mute film made by Wallace Chafe,

see Chafe (1980)) and “Frog Stories” (8 narratives from a sketch book by Mayer

(1980)). An example of an original data segment follows:

(2)

9. ... (1.7) m-wa:i' 'aehae' ka

AF-comeone NOM

10. ...(1.1) ma'iaeh ima h<oem>oehoe' ka siri'

person ASP <AF>pull ACC goat

11. ... may hiza

pass.by[AF] there


12. ...(1.9) ilahiza kabih

move.to.that.place side

“(The man pulling a goat) passed by this way and went that way.” (Pear 3:9-

12)

Spoken corpus, in contrast to written corpus, is composed of utterances shorter or

equal to sentences, which are transcribed according to certain criteria, such as turn-

taking, pause, and ruptures in intonation contours of monologue (Tao 1996:35). Fig.

1. shows a unified intonation contours in a praat3 window.

Fig. 1. A unified intonation contour

When a corpus is transcribed, tagged and analyzed, one needs to look for a means

to make it accessible to the public. An integrated platform to store, to represent and

to lower the technological boundaries for further use of the collected data is thus

necessary. With the insufficiencies of the Sinica archive in mind, normalization,

accessibility and interoperability are emphasized in the design of our system. The

following guidelines are thus proposed.

3 praat is a programmable phonetic analyser written by Paul Boersma and David Weenink, Institute of Phonetic Sciences, University of Amsterdam. It is licensed in GNU Public License, with the courtesy of their outrageous work and the free software. Cf. http://www.fon.hum.uva.nl/praat/


(3) Guidelines of the integrated platform

(a) Easy to customize for most Austronesian languages

(b) Standardized procedures of transcription, annotation and process

(c) Automatic extraction of morphosyntactic information to reduce

repetition of human labor

(d) Web-based, unified input/output interface

(e) Searchable corpus that fit the needs of both linguists and the public

(f) Multimedia representation of collected texts

(g) Interoperable with other systems

(h) Cross-platform, operating system independent

Below is a description of the input, processing and output of our system design.

3.1 Standardization of text commitment and standards of committed texts

The standardization comprises the procedure of handling transcribed texts, the tran-

scription itself and morphosyntactic and discoursal codes used in the transcription.

The procedure to handle collected texts is designed with low coupling in order to re-

duce complexity. Therefore, the dependence in human manipulation in the system is

almost uni-directional, as can be seen in Figure 2. Whenever a spoken text is collec-

ted, some worker transcribes it. Once the transcription is complete, it is given to the

database maintainer for processing and storage. The web interface shows the corpus

in the database, so that people on the other end of Internet can browse and search the

corpus.


Fig. 2. Use cases of the system

The transcription follows Du Bois (1993), a de facto standard in the linguistic

community. Word glosses and annotations follow a standardized coding list inherited

from conventional mark-ups (cf. Appendix A) and the Leipzig glossing rules4. A

standard operation is also set for the database maintainer to handle fieldwork

collections as shown in Figure 3.

4 http://www.eva.mpg.de/lingua/files/morpheme.html


Fig.3. Standard operation of text commitment

The corpus in our system is stored in Unicode (UTF-8 encoding) for potential

need of IPA, Japanese, and annotations in other languages. If some of the tribes

decide to adopt non-ASCII letters, such as “ ɖ ʈ ɼ ɫ ʔ ”, into their writing systems, the

programs can process them correctly with no need of modification. As Unicode

BOM (byte-order-mark, U+FEFF) is appended in the beginning of the file in

Microsoft Windows and is absent in Unix-based systems, the mark may cause a

potential problem in reading files edited in different operating systems. It is properly

dealt with in order to fulfil the criteria of platform-independence.

A set of metadata is defined in the head of committed files. An example of

the head of a committed text is given in (4) and the description of the fields is shown

in Table 1.

(4)

Topic: Pear story


Type: Narrative

Language: Kavalan

Dialect: Xinshe

Speaker: Imui, 潘金妹, F,1952

Time: 00:01:15

Total IUs: 31

Collected: 2003-05-30

Revised: 2003-11-11

Transcribed by: 葉俞廷, 王以勤Double checked: 鍾曉芳,沈嘉琪 ,葉俞廷

Table 1. Metadata of committed dataField name Description Format

Topic Topic of text String (e.g., Pear Story)

Type Style of text Narrative|Conversation|...

Language Language of text String, first letter in capital

Dialect Dialect or district String

Speaker Base data of the informant Native/Chinese name, Gender, Age

Time Length of recording hh:mm:ss

Total IUs Number of IUs in text Numeric


Field name Description Format

Collected Date of recording yyyy-mm-dd

Revised Date of latest revision yyyy-mm-dd

Transcribed by Transcribers and annotaters Comma separated string

Double checked Inspectors of text Comma separated string

The text following the metadata is described below.

(5)

5. [IU #, with a period in the end]

.. qay- .. qay-byabas 'nay ,_ [words separated by spaces]

QAY-guava that [English gloss separated by spaces]

QAY-芭樂那 [Chinese gloss separated by spaces]

6.

... razat 'nay nani.\

person that DM

人那 DM

#e That person picked guavas. Then,

#c 那個人採芭樂。然後，#n Elicitaion notes

#n (More elicitation notes)

Lines beginning with a sharp (#) are processor instructions (PI). “#e” indicates a


line of English translation of a paragraph composed of the IUs from the last

translation to the current one. “#c” marks a Chinese translation, and “#n” is

elicitation notes. It is possible to have more than one note. The alignment of native

words and glosses is automatically done. Morpheme boundaries, morphological

information and word senses are extracted using the techniques introduced in Lin

(2005: Chapters 2 and 4.2).

As the transcription is supposed to more or less reflect actual pronunciation of an

informant, spelling may vary slightly from word to word. For the system not to be

confused by these variations, a feature vector is configured for each formosan

language. A vector describes how to reduce the variants into a simpler form. For

example, the pronunciation of a and ae is quite similar in Saisiyat, and glottal-stops

are sometimes omitted. 'aehae' “one” is usually spelled 'ahae or aehae. Below are

feature vectors of Saisiyat and Kavalan.5

Saisiyat: ae → a, oe → o, S → s, ' → ∅Kavalan: th → l, d → l, ' → ∅

A string substitution is executed before any operation in the database in order to

prevent possible duplicated entries; otherwise full-text search may fail to work.

3.2 Database design

Database design affects the efficiency in search and storage. For simplifying

programming logic and high-speed query, we proposed a schema that differs from the

Sinica archive. Every relational database engine that follows the SQL92 standard can

be used in the implementation of the schema. SQLite6, among relational database

systems, is recommended for the following reasons:

5 Kavalan is an Austronesian language spoken in Hualien County, east Taiwan.6 http://www.sqlite.org


1. It is light-weight, fast and platform independent.

2. A database is stored in a single file, thus is easy to maintain.

3. It supports UTF-8 encoding.

4. It is a free software.

One formosan language is placed in one database and is thus stored in a single

file. The schema of every language should be the same, therefore cross-linguistic

search can be executed in a single page. It is often argued that a database has to be

normalized to the third level.7 To be realistic, our system is designed for the sake of

efficiency. The relational diagram of tables in the database is shown in Figure 4. A

full list of database schema is given in Appendix B.

7 There is a good tutorial about database normalization at http://dev.mysql.com/tech-resources/articles/intro-to-normalization.html


Fig.4. Relational diagram of tables in the database

The text is mainly stored in Table “iu”. In contrast to the word-based design in

the Sinica archive, every intonation unit is stored in one row. For example,

article : pear3

nat : ...(1.2) ima h-oem-angaw kasna'itol ray kahoey babaw

sim : . ima homangaw kasnaitol ray kahoy babaw

eng : . Asp set_a_ladder-AF move_up-AF Loc tree above

For a full-text search, a simple query of “%keyword%” to every field listed

above returns the correct results. The simplified spelling is stored for searching

among spelling variants. Words in the database are separated by a single space, so


that they are easily processed in programs by a single function (explode () in PHP and

split () in Python). Places where no gloss is available are occupied by a period (“.”);

thus, words and glosses are always aligned across the fields.

Another specialized data structure is designed in Table “lemma”. In order to

properly search an affix, the stem is marked for every word in the dictionary. The

morpheme before the stem is a prefix and the one after it a suffix. For example,

Saisiyat kapapama'an 'bicycle' is stored as ka-#papama'#-an in the table. If one looks

for a prefix ka- or a suffix -an, one can always obtain the right answer by taking the

elements before the first sharp (#) or after the second sharp. Since infixation is simple

in the two languages, it is currently analyzed on the fly by external programs.8

3.3 Back-end programs and the POS-tagger

Database maintainer commits a pre-processed transcription into the database through

a batch of back-end programs. Commitment is preferably done in the command-line,

so that mismatches in alignment or failure of automated morphological analysis may

be corrected immediately and interactively. A prototype is implemented to prove the

workability of the system. Here is a list of programs.

features.py

defines language-specific feature-vectors and provides connection DSN.

simplify.py

is the common library for reducing spelling variants.

canon.py

checks input validity, including metadata and text format. It writes the data

into the database when the check passes.

extractmorph.py

defines morphological and discoursal codes and extracts them from the texts.

8 After the corpus complies with the Leipzig glossing rules, infixation will be marked by < and >.


makedict.py

extracts information from imported texts and updates the dictionary.

mp3splt.py/mpgsplt.py

splits .mp3 / .mpg files according to the time-file (see below).

tidy.py

utility to convert Chinese punctuation into ASCII and remove unnecessary

Microsoft Word mark-ups.

The coupling of the modules is fairly low. “features.py” and “simplify.py”

provide the necessary functions for all programs.

As texts have been put into the database, they are tagged by a TBL tagger (cf. Lin

2005: Chapter 2), and the dictionary is updated at the same time. When a user looks

up a word, the part-of-speech information can be obtained along with its frequency in

the corpus. Any time the database maintainer finds an error in the tagged corpus, it

can be corrected on-line as an immediate feedback to the tagger. The tagger can later

be retrained by a single click.

3.4 Unified output interface

For the corpus to be accessible to the public, a unified user-friendly interface is built.

The system follows HTML 4.01 (loose) proposed by the World-Wide Web

Consortium9 and is designed to be browsed with a browser, because this is one of the

major means to access data from the Internet. For a dynamic and interactive

representation, the Document Object Model (DOM)10 and JavaScript 1.2 are

preferably used. Popular browsers, such as Internet Explorer 5.0, Mozilla 1.7, Firefox

0.9 and Opera 4, are compliant to these standards. It is important to support major

browsers for the purpose of accessibility. Figure 5 is a screen dump of the web site

under construction.

9 http://www.w3.org/TR/REC-html40/10 http://www.w3.org/DOM/


Fig.5. Screen dump of the web site (under construction)

The interface is composed of the following parts: a window with the informant's

photo where movie clips are played, a list of metadata in the upper-left corner, several

switches to adjust browsing effects and a frame in the bottom of the screen to dump

the selected article in a format following linguistic convention. A dictionary is

popped-up anytime when a user clicks on an unknown word (see Figure 6). The

pages are being revised for a better visual effect.

Ethnological notes and examples are preferably given in the dictionary with

cross-reference. The design for an interface for searching is simple, yet complicated

and special linguistic needs are still possible. For example, by typing tabatathan a

user can find the occurrences of the Kavalan word ta-batad-an; typing 'ahae or aehae


results in 'aehae' for Saisiyat, and so on. Interfaces to user-defined functions (UDF)

are also kept for further improvement.


Fig. 6. Pop-up dictionary with cross-references

As the bandwidth is quite limited, it is suggested that multimedia data are stored

and transferred in the formats of 16Kbps 11kHz MPEG-1 layer 3 for audio data and

MPEG-1 for video data.

3.5 Interoperability

It is important to share the corpus with the linguistic community. The Extensible

Mark-up Language (XML)11 is a simple and flexible language used to exchange data

between different systems. It is now a de facto standard on the web. For researchers

of natural language processing to easily profit from our collected data, the corpus

should be able to be exported in XML. Morphological information, gloss and part-of-

speech of every word may be output in a uniform manner. An exported format is

given below.

11 http://www.w3.org/XML/


<?xml version="1.0" encoding="utf-8" ?>

<article id="pear_imui">

<topic>Pear Story</topic>

<language>Kavalan</language>

<dialect>Xinshe</dialect>

<speaker>

<natname>imui</natname>

<chnname>潘金妹</chnname>

<gender>F</gender>

<age-of-record>51</age-of-record>

</speaker>

<duration>00:01:15</duration>

<total-iu>31</total-iu>

<collected>2003-05-30</collected>

<revised>2003-11-11</revised>

<transcriber>葉俞廷</transcriber>

<transcriber>王以勤</transcriber>

<doublecheck>鍾曉芳</doublecheck>

<doublecheck>沈嘉琪</doublecheck>

<doublecheck>葉俞廷</doublecheck>

<text>

<iu id="iu_1">

<word>

<nat>tangi</nat>

<sim>tangi</sim>

<eng>today</eng>

<chn>今天</chn>

<pos>RB</pos>

</word>


<word>

...

</word>

</iu>

<iu id="iu_2"> ... </iu>

...

<para von="1" bis="4">

<eng>I just saw a person there ...</eng>

<chn>我剛剛看到 ...</chn>

<notes>Some elicitation notes</notes>

</para>

...

</text>

</article>

4 Conclusive Remarks

The online version of NTU corpus of Austronesian languages is still under

construction and more texts are to be added. The adaptation of the Leipzig glossing

rules will be adopted in the near future. As normalization, accessibility and

interoperability are emphasized for the system, it should be useful and helpful for

linguists, teachers and even native speakers of Austronesian languages. It is hoped

that our work could contribute to the language communities. The system is

extendible for the processing of other languages once the proper feature vector is set.

The implementation is still on its experimental stage. As Saisiyat and most Formosan

languages are on the verge of being endangered, more people are urged to participate,

to use and to promote the enlargement of the corpora.


Appendix A. Coding Lists

Table 2. Morphological coding list

English code Chinese code Description

1SG 1SG 1st person singular

2SG 2SG 2nd person singular

3SG 3SG 3rd person singular

1IPL.NOM 1IPL.主格 1st person plural, Inclusive, Nominative

1EPL.NOM 1EPL.主格 1st person plural, Exclusive, Nominative

1PL 1PL 1st person plural

2PL 2PL 2nd person plural

3PL 3PL 3rd person plural

ACC 受格 Accusative

AF 主焦 Agent Focus

ASP 動貌 Aspect

AUX 助動詞 Auxiliary

BC BC Back Channel / Reactive Token

BF 予焦 Benefactive Focus

CAU 使役 Causative

CLF 量詞 Classifier

CLF.HUM 人量詞 Human Classifier

CLF.NHUM 非人量詞 Non-human Classifier

COM ? Comitative

COMP 補語詞 Complementizer

COND 條件詞 Conditional Marker

DAT 予格 Dative


DEF 定指 Definite

DET 限定詞 Determiner

DIST 遠距 Distal

DM DM Discourse Marker

EXCL 排除 Exclusive

EXIST 存在 Existential

EXPER 經驗 Experiential

FIL FIL Pause Filler

FS FS False Start

FUT 未來 Future

GEN 屬格 Genitive

IF 工焦 Instrumental Focus

IMP 祈使 Imperative

INCL 包含 Inclusive

INDF 不定指 Indefinite

INS 工具格 Instrument

INT 感嘆 Interjection

INVIS 不可見 Invisible

IRR 非實現 Irrealis

LF 處焦 Locative Focus

LNK 連詞 Linker

LOC 處格 Locative

NCM Ncm Non-common Name Marker

NEG 否定 Negative

NEU 中性格 Neutral

NMZ 名物化 Nominalizer/Nominalization

NOM 主格 Nominative

NRFUT 即將 Near Future


OBL 斜格 Oblique

PF 受焦 Patient Focus

PFV 完成 Perfective

PN 人名/地名 proper name/place name

POSS 所有格 Possessive

PROG 進行 Progressive

PROX 近距 Proximal/Proximate

Q 疑問 Question Marker

QUOT QUOT Quotative

REC 交互 Reciprocal

RED 重疊 Reduplication

REL 關係詞 Relativizer

REFL 反身 Reflexive

RF 指焦 Referential Focus

TOP 主題 Topic

VIS 可見 Visible

VOC 呼格 Vocative

X X Uncertain Hearing

TU TU

mazmun many.HUM many (humans)

mwaza many.NHUM many (animals)

this 這個that 那個

Table 3. Discourse coding list (adopted from Du Bois (1993))

Meaning Marker

Units

Intonation Unit ((newline))


Meaning Marker

Truncated IU --

Word ((space))

Truncated word -

Speaker identity / turn start :

Speech Overlap [ ]

Transitional Continuity

Final .

Continuing ,

Appeal ?

Terminal Pitch Direction

Fall \

Rise /

Level _

Accent and Lengthening

Primary accent ^

Secondary accent `

High booster !

Low booster ;

Lengthening = =

Tone

Fall \


Meaning Marker

Rise /

Fall-Rise \/

Rise-fall /\

Level _

Pause

Long ...(N)

Medium ...

Short ..

Latching 0

Vocal Noises

Vocal noises (CAPITAL LETTERS)

Inhalation (H)

Exhalation (Hx)

Glottal stop %

Laughter @

Quality

Quality <Y Y>

Laugh quality <@ @>

Quotation quality <Q Q>

Phonetics

Phonetic / phonemic transcription (/ /)


Meaning Marker

Transcriber's Perspective

Researcher's comment (( ))

Uncertain hearing <X X>

Indecipherable syllable X

Specialized Notations

Duration (N)

IU boundary &

Accent unit boundary |

Embedded IU <| |>

Restart {Capital Initial}

False start < >

Code switching <L2 L2>

Nontranscription line $

Reserved Symbols

Phonetic / orthographic symbols '

Morphosyntactic coding + * # { }

User-definable symbols " ~

Appendix B. Database Schema

Table meta: metadata of text


Field name Format Description Example

article varchar(80) Filename pear_imui

topic varchar(80) Text name Pear Story

texttype varchar(40) Text style narrative

language varchar(40) Text language Kavalan

dialect varchar(40) Dialect or district Xinshe

spknat varchar(80) Native name of Informant imui

spkhan varchar(80) Chinese name of Informant 潘金妹spkgdr char(1) Gender of Informant (M|F) F

spkage integer Age of Informant in time of recording 51

duration time Length of the recording 00:01:15

totaliu integer Number of intonation units 31

collected date Date of record 05/5/30

revised date Date of last revision 03/11/11

transcr blob Comma separated names of

transcribers

A, B, C

dblchk blob Names of people who double check the

text

D, E, F

Table iu: storage of a single intonation unitField name Format Description

article varchar(80) Text name (foreign key of meta.article)

no integer IU #


Field name Format Description

nat blob Native words, space separated

sim blob Simplified native words

eng blob English gloss, space separated

chn blob Chinese gloss, space separated

Table para: translation of a block of intonation unitsField name Format Description

article varchar(80) Text name (foreign key of meta.article)

von integer IU# where the block begins

bis integer IU# where the block ends

eng blob English translation

chn blob Chinese translation

note blob Elicitation notes (multi-line, separated by two semi-

colons)

Table dict: the dictionaryField name Format Description

word varchar(80) Word of index (simplified word)

lemma blob Word forms, comma separated

eng blob English gloss with morphological marks

chn blob Chinese gloss with morphological marks

note blob Notes (multi-line, separated by two semi-colons)

ex blob Example of how the word is used


Table lemma: analyse of a lemmaField name Format Description

word varchar(80) Lemma of a word (foreign key to an element of

dict.lemma)

lemma varchar(80) Prefix-#stem#-suffix

enmorph varchar(255) Morphological marks in English, comma separated

zhmorph varchar(255) Morphological marks in Chinese, comma separated

enstem varchar(255) Sense of the stem in English, comma separated

zhstem varchar(255) Sense of the stem in Chinese, comma separated

Table affix: dictionary of affixesField name Format Description

affix varchar(20) Affix (prefix-, -infix-, -suffix)

englos varchar(255) Morphological analyse in English

zhglos varchar(255) Morphological analyse in Chinese

note blob Notes

Table xref: cross-reference of a wordField name Format Description

word varchar(80) Word (simplified)

xref blob Article:IU#.number_of_word


References

Chafe, Wallace L. ed. 1980. The pear stories: Cognitive, cultural, and linguistic

aspects of narrative production. Norwood, NJ: Ablex Publishing Corp.

Du Bois, J. W. 1993. Talking data: Transcription and coding in discourse research,

chapter Outline of discourse transcription, 45-89. NJ: Hillsdale: Lawrence

Erlbaum Associates.

Huang, Shuan-Fan, Lily I-wen Su, and Li-May Sung. 2003. Syntax and cognition in

SaiSiyat. NSC 93-2411-H-022-094.

Lin, Zhemin. 2005. Automatic processing of languages with small-scaled corpus:

Part-of-speech tagging and partial parsing saisiyat and applications. Master's

thesis, National Taiwan University.

Luhn, H. P. 1960. Keyword-in-context index for technical literature (kwic index).

American Documentation 11:288-295.

Mayer, Mercer. 1980. Frog, where are you?. NY: Dial Books.

Tao, Hongyin. 1996. Units in mandarin conversation: Prosody, discourse and

grammar. Amsterdam: John Benjamins.

Zeitoun, Elizabeth, Ching hua Yu, and Cui xia Weng. 2003. The formosan language

archive: Development of a multimedia tool to salvage the languages and oral

traditions of the indigenous tribes of taiwan. Oceanic Linguistics 42(1):218-

232.

Zeitoun, Elizabeth, and Ching-Hua Yu. 2005. The formosan language archive:

Linguistic analysis and language processing. Computational Linguistics and

Chinese Language Processing 10(2):167-200

design of a multimedia corpus of austronesian linguisticsciet/form/paper/4.doc · web view 3.2...

Documents