Steven Bird

Designing and Evaluating an XPath Dialect for Linguistic Queries

Publisher: IEEE

Date: 2006

DOI: 10.1109/ICDE.2006.48

Presenting autosegmental phonology

Publisher: Cambridge University Press (CUP)

Date: 03-1991

DOI: 10.1017/S0022226700012469

14 Dschang syllable structure

Publisher: De Gruyter Mouton

Date: 31-12-1999

DOI: 10.1515/9783110806793.447

Building a search engine to drive problem-based learning

Publisher: ACM

Date: 26-06-2006

DOI: 10.1145/1140124.1140166

Querying databases of annotated speech

Publisher: IEEE Comput. Soc

Date: 2000

DOI: 10.1109/ADC.2000.819808

Designing to Support Remote Working Relationships with Indigenous Communities

Publisher: ACM

Date: 30-11-2021

DOI: 10.1145/3520495.3520522

Phonology

Publisher: Oxford University Press

Date: 07-03-2018

DOI: 10.1093/OXFORDHB/9780199573691.013.30

Abstract: Phonology is the systematic study of the sounds used in language, their internal structure, and their composition into syllables, words, and phrases. Computational phonology is the application of formal and computational techniques to the representation and processing of phonological information. This chapter presents the fundamentals of phonology along with an overview of computational phonology. Fundamentals discussed include phonological features, phonemes, early generative grammar, autosegmental phonology, syllable structure, and optimality theory. Finite-state machines, attribute-value matrices, computational learning methods, and existing software toolkits round out the discussion on comptuational phonology.

Learning Crosslingual Word Embeddings without Bilingual Corpora

Publisher: Association for Computational Linguistics

Date: 2016

DOI: 10.18653/V1/D16-1136

The Open Language Archives Community: a 20-year update

Publisher: Emerald

Date: 23-11-2022

DOI: 10.1108/EL-08-2022-0192

Abstract: This paper reports on the first 20 years of the Open Language Archives Community (OLAC), comprehensive infrastructure for indexing and discovering language resources. We begin with the original vision, assess progress relative to the original requirements, and identify ongoing challenges. Based on the overview of OLAC history and recent developments and on the analysis of the situation in the language archives area as a whole, the authors propose an agenda for a more sustainable future for open language archiving. This paper examines the progress of OLAC and discusses improvements in such areas as participation, access, and sustainability.

Orthography and identity in Cameroon

Publisher: John Benjamins Publishing Company

Date: 08-11-2001

DOI: 10.1075/WLL.4.2.02BIR

Abstract: The tone languages of sub-Saharan Africa raise challenging questions for the design of new writing systems. Marking too much or too little tone can have grave consequences for the usability of an orthography. Orthography development, past and present, rests on many sociolinguistic issues having little to do with the technical phonological concerns that usually preoccupy orthographers. Some of these issues are familiar from the spelling reforms which have taken place in European languages. However, many of the issues faced in sub-Saharan Africa are different, being concerned with the creation of new writing systems in a multi-ethnic context — involving residual colonial influences, the construction of new nation-states, detribalization vs. culture preservation and language reclamation. Language development projects which crucially rely on creating or revising orthographies may founder if they do not attend to the various layers of identity (colonial, national, ethnic, local, or in idual) that are indexed by orthography. This study reviews the history and politics of orthography in Cameroon, with a focus on tone-marking. The article concludes by calling present-day orthographers to a deeper and broader understanding of orthographic issues.

A Neural Network Model for Low-Resource Universal Dependency Parsing

Publisher: Association for Computational Linguistics

Date: 2015

DOI: 10.18653/V1/D15-1040

Sparse Transcription

Publisher: MIT Press - Journals

Date: 02-2021

DOI: 10.1162/COLI_A_00387

Abstract: The transcription bottleneck is often cited as a major obstacle for efforts to document the world’s endangered languages and supply them with language technologies. One solution is to extend methods from automatic speech recognition and machine translation, and recruit linguists to provide narrow phonetic transcriptions and sentence-aligned translations. However, I believe that these approaches are not a good fit with the available data and skills, or with long-established practices that are essentially word-based. In seeking a more effective approach, I consider a century of transcription practice and a wide range of computational approaches, before proposing a computational model based on spoken term detection that I call “sparse transcription.” This represents a shift away from current assumptions that we transcribe phones, transcribe fully, and transcribe first. Instead, sparse transcription combines the older practice of word-level transcription with interpretive, iterative, and interactive processes that are amenable to wider participation and that open the way to new methods for processing oral languages.

Stochastic modelling of ecological processes using hybrid Gibbs samplers

Publisher: Elsevier BV

Date: 09-2006

DOI: 10.1016/J.ECOLMODEL.2006.04.008

Building an Open Language Archives Community on the OAI foundation

Publisher: Emerald

Date: 06-2003

DOI: 10.1108/07378830310479848

Abstract: The Open Language Archives Community (OLAC) is an international partnership of institutions and in iduals who are creating a worldwide virtual library of language resources. The Dublin Core (DC) Element Set and the OAI Protocol have provided a solid foundation for the OLAC framework. However, we need more precision in community‐specific aspects of resource description than is offered by DC. Furthermore, many of the institutions and in iduals who might participate in OLAC do not have the technical resources to support the OAI protocol. This paper presents our solutions to these two problems.

Decolonising Speech and Language Technology

Publisher: International Committee on Computational Linguistics

Date: 2020

DOI: 10.18653/V1/2020.COLING-MAIN.313

Learning a Lexicon and Translation Model from Phoneme Lattices

Publisher: Association for Computational Linguistics

Date: 2016

DOI: 10.18653/V1/D16-1263

Learning Through Transcription

Publisher: Association for Computational Linguistics

Date: 2022

DOI: 10.18653/V1/2022.COMPUTEL-1.11

Understanding how language revitalisation works: a realist synthesis

Publisher: Informa UK Limited

Date: 25-10-2022

DOI: 10.1080/01434632.2022.2134877

Phonology

Publisher: Oxford University Press

Date: 18-09-2012

DOI: 10.1093/OXFORDHB/9780199276349.013.0001

Abstract: This article presents the fundamentals of descriptive phonology and gives an overview of computational phonology. Phonology is the systematic study of sounds used in language, and their composition into syllables, words, and phrases. It introduces some of the key concepts of phonology by simple ex les involving real data and gives a brief discussion of early generative phonology. It analyses the autosegmental phonology using some data from African tone language. This article considers in detail one level of phonological hierarchy, namely, the syllable. It reveals many interesting issues that are confronted by phonological analysis. Some of these theoretical frameworks include: lexical phonology, underspecification phonology, government phonology, declarative phonology, and optimality theory. The article provides a means for phonological generalizations such as rules and constraints to give a finite-state interpretation.

What Can We Get From 1000 Tokens? A Case Study of Multilingual POS Tagging For Resource-Poor Languages

Publisher: Association for Computational Linguistics

Date: 2014

DOI: 10.3115/V1/D14-1096

The Open Language Archives Community: An Infrastructure for Distributed Archiving of Language Resources

Publisher: Oxford University Press (OUP)

Date: 06-2003

DOI: 10.1093/LLC/18.2.117

Learning a Translation Model from Word Lattices

Publisher: ISCA

Date: 08-09-2016

DOI: 10.21437/INTERSPEECH.2016-862

“We are reconciliators”: When Indigenous tourism begins with agency

Publisher: Informa UK Limited

Date: 13-04-2022

DOI: 10.1080/09669582.2021.1903908

“We are reconciliators”: when Indigenous tourism begins with agency

Publisher: Routledge

Date: 29-11-2022

DOI: 10.4324/9781003299578-10

Accessing the spoken word

Publisher: Springer Science and Business Media LLC

Date: 08-2005

DOI: 10.1007/S00799-004-0101-0

An Attentional Model for Speech Translation Without Transcription

Publisher: Association for Computational Linguistics

Date: 2016

DOI: 10.18653/V1/N16-1109

Teaching Computer Science in the Victorian Certificate of Education

Publisher: ACM

Date: 08-03-2017

DOI: 10.1145/3017680.3017735

A framework for annotating animal bioacoustic data

Publisher: Acoustical Society of America (ASA)

Date: 05-2001

DOI: 10.1121/1.4744600

Abstract: Annotation graphs (AGs) provide an efficient and expressive data model for linguistic annotations of time–series data [Bird and Liberman, 2001]. The term annotation here refers to the association of structured symbolic information with an extent of signal data. This paper demonstrates that AGs also provide an excellent framework for annotating time–series animal bioacoustic data. The AG model has several desirable properties for annotating animal bioacoustic signals. Partial or incomplete annotations can be represented naturally. Hierarchical structures, such as internal structures of animal communicative signals, can be stored and manipulated effectively. The model permits efficient query using the relational database technology. The spreadsheet-like editor component described in the paper provides an intuitive user interface for creating annotations of bioacoustic signals, such as monkey vocalizations, as AG data. The paper describes the tool used for annotating the vocalization of vervet monkeys, and the preliminary findings of the project are presented. Finally, the paper lays out a complete infrastructure for supporting the rapid development of annotation tools for animal bioacoustic data [S. Bird and M. Liberman, ‘‘A Formal Framework for Linguistic Annotation,’’ Speech Commun. 33, 23–60 (2001)].

Feature structures and indices

Publisher: Cambridge University Press (CUP)

Date: 05-1991

DOI: 10.1017/S0952675700001305

Abstract: Hayes (1990) proposes the adoption of a new notation for representing hierarchical phonological structure, in response to a notational problem which he calls the DIPHTHONGISATION PARADOX. More generally, he seeks to find a replacement for the current method of depicting feature trees, which is not ideally suited to the clear expression of rules and derivations. While I am in complete agreement with this standpoint and fully support Hayes' assertion that certain ambiguities of interpretation have crept into the graphical conventions currently in widespread use, I nevertheless believe his proposal suffers from a number of problems. Once identified, these problems can be solved with further notational and formal refinements.

A Scalable Method for Preserving Oral Literature from Small Languages

Publisher: Springer Berlin Heidelberg

Date: 2010

DOI: 10.1007/978-3-642-13654-2_2

Local Languages, Third Spaces, and other High-Resource Scenarios

Publisher: Association for Computational Linguistics

Date: 2022

DOI: 10.18653/V1/2022.ACL-LONG.539

Strategies for Representing Tone in African Writing Systems

Publisher: John Benjamins Publishing Company

Date: 23-07-1999

DOI: 10.1075/WLL.2.1.02BIR

Abstract: Tone languages provide some interesting challenges for the designers of new orthographies. One approach is to omit tone marks, just as stress is not marked in English (zero marking). Another approach is to do phonemic tone analysis, and then make heavy use of diacritic symbols to distinguish the "tonemes" (shallow marking). While orthographies based on either system have been successful, this may be thanks to our ability to manage inadequate orthographies, rather than to any intrinsic advantage which is afforded by one or the other approach. In many cases, practical experience with both kinds of orthography in sub-Saharan Africa has shown that people have not been able to attain the level of reading and writing fluency that we know to be possible for the orthographies of non-tonal languages. In some cases this can be attributed to a socio linguistic setting which does not favour vernacular literacy. In other cases, the orthography itself may be to blame. If the orthography of a tone language is difficult to use or to learn, then a good part of the reason may be that the designer either has not paid enough attention to the FUNCTION of tone in the language, or has not ensured that the information encoded in the orthography is ACCESSIBLE to the ordinary (non-linguist) user of the language. If the writing of tone is not going to continue to be a stumbling block to literacy efforts, then a fresh approach to tone orthography is required — one which assigns high priority to these two factors. This article describes the problems with orthographies that use too few or too many tone marks, and critically evaluates a wide range of creative intermediate solutions. I review the contributions made by phonology and reading theory, and provide some broad methodological principles to guide those who are seeking to represent tone in a writing system. The tone orthographies of several languages from sub-Saharan Africa are presented throughout the article, with particular emphasis on some tone languages of Cameroon.

When Marking Tone Reduces Fluency: An Orthography Experiment in Cameroon

Publisher: SAGE Publications

Date: 03-1999

DOI: 10.1177/00238309990420010401

Abstract: Should an alphabetic orthography for a tone language include tone marks? Opinion and practice are ided along three lines: zeromarking, phonemic marking and various reduced marking schemes. This paper examines the success of phonemic tone marking for Dschang, a Grassfields Bantu language which uses tone to distinguish lexical items and some grammatical constructions. Participants with a variety of ages and educational backgrounds, and having different levels of exposure to the orthography, were tested on location in the Western Province of Cameroon. All but one had attended classes on tone marking. Participants read texts which were marked and unmarked for tone, then added tone marks to the unmarked texts. Analysis shows that tone marking degrades reading fluency and does not help to resolve tonally ambiguous words. Experienced writers attain an accuracy score of 83.5% in adding tone marks to a text, while inexperienced writers score a mere 53%, which is not much better than chance. The experiment raises serious doubts about the suitability of the phonemic method of marking tone for languages having widespread tone sandhi effects,and lends support to the notion that a writing system should have "fixed word images.” A critical review of other experimental work on African tone orthography lays the ground work for the experiment, and contributes to the establishment of a uniform experimental paradigm.

Speech annotation and corpus tools

Publisher: Elsevier BV

Date: 2001

DOI: 10.1016/S0167-6393(00)00066-2

Seven dimensions of portability for language documentation and description

Publisher: Project MUSE

Date: 2003

DOI: 10.1353/LAN.2003.0149

Phonological events

Publisher: Cambridge University Press (CUP)

Date: 03-1990

DOI: 10.1017/S0022226700014419

Abstract: One of the major innovations within post-SPE generative phonology has been the development of frameworks where phonological units are organized in a non-linear fashion. Taking autosegmental phonology (Goldsmith, 1976) as our main exemplar of such frameworks, we wish to address the following question: What is the appropriate interpretation of autosegmental representations? There is, of course, a further question about what we mean by INTERPRETATION: formal, phonetic or computational interpretation? Although we will concentrate on the first of these, we believe that all three aspects should be regarded as closely inter-connected and mutually constraining. The question of interpreting autosegmental representation has in fact been recently posed by Sagey (1988), and we shall take her proposal as our starting point. While it is uncontroversial to suppose that the relationship between units on a given autosegmental tier is one of temporal precedence, Sagey claims that it is more problematic to pin down what is meant by association between tiers. She argues, cogently we believe, that if association is taken to be a relationship of simultaneity between durationless units, then standard analyses of complex segments and gemination lead to logical inconsistency. Instead, association should be taken as temporal OVERLAP between units with duration.

Low Resource Dependency Parsing: Cross-lingual Parameter Sharing in a Neural Network Parser

Publisher: Association for Computational Linguistics

Date: 2015

DOI: 10.3115/V1/P15-2139

Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

Publisher: The MIT Press

Date: 07-01-2020

DOI: 10.7551/MITPRESS/10990.001.0001

Abstract: Making erse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making erse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and erse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. The open access edition of this book was made possible by generous funding from Knowledge Unlatched. ContributorsIsabelle Barrière, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zinn

Bad but Bold: Ambivalent Attitudes Toward Men Predict Gender Inequality in 16 Nations

Publisher: American Psychological Association (APA)

Date: 2004

DOI: 10.1037/0022-3514.86.5.713

A formal framework for linguistic annotation

Publisher: Elsevier BV

Date: 2001

DOI: 10.1016/S0167-6393(00)00068-6

Extending Prolog to Provide Better Support for Design Code Expert Systems

Publisher: Wiley

Date: 06-1988

DOI: 10.1111/J.1467-8667.1988.TB00160.X

Maximizing intake under challenging foraging conditions at two spatial scales in Soay sheep

Publisher: Elsevier BV

Date: 02-2007

DOI: 10.1016/J.ANBEHAV.2006.05.015

The OLAC metadata set and controlled vocabularies

Publisher: Association for Computational Linguistics

Date: 2001

DOI: 10.3115/1118062.1118065

Developing a Suite of Mobile Applications for Collaborative Language Documentation

Publisher: Association for Computational Linguistics

Date: 2017

DOI: 10.18653/V1/W17-0121

Finite-state phonology in HPSG

Publisher: Association for Computational Linguistics

Date: 1992

DOI: 10.3115/992066.992081

A logical approach to Arabic phonology

Publisher: Association for Computational Linguistics

Date: 1991

DOI: 10.3115/977180.977196

Querying Linguistic Trees

Publisher: Springer Science and Business Media LLC

Date: 28-05-2009

DOI: 10.1007/S10849-009-9086-9

Extending Dublin Core metadata to support the description and discovery of language resources

Publisher: Springer Science and Business Media LLC

Date: 2003

DOI: 10.1023/A:1025720518994

Bootstrapping Techniques for Polysynthetic Morphological Analysis

Publisher: Association for Computational Linguistics

Date: 2020

DOI: 10.18653/V1/2020.ACL-MAIN.594

Collective Document Classification with Implicit Inter-document Semantic Relationships

Publisher: Association for Computational Linguistics

Date: 2015

DOI: 10.18653/V1/S15-1012

Cross-lingual Transfer for Unsupervised Dependency Parsing Without Parallel Data

Publisher: Association for Computational Linguistics

Date: 2015

DOI: 10.18653/V1/K15-1012

Selecting nonlinear stochastic process rate models using information criteria

Publisher: Elsevier BV

Date: 12-2112

DOI: 10.1016/J.PHYSD.2005.11.007

Designing Mobile Applications for Endangered Languages

Publisher: Oxford University Press

Date: 08-08-2018

DOI: 10.1093/OXFORDHB/9780190610029.013.40

Abstract: Speakers of the world’s endangered languages are rapidly gaining access to broadband internet on mobile devices. Meanwhile, social mobile technologies continue to transform the way people work together. I believe that conditions are ripe for the development of a new generation of software for endangered languages. This software will enable new ways for linguists to collaborate with speakers in ancestral homelands and worldwide diasporas to produce high-quality large-scale documentation. This chapter sets out a conceptual framework and describes some concrete steps for designing mobile applications for endangered languages, recognizing the special challenges they present, such as reliance on oral materials, lack of established orthography, and lower digital literacy.

Multilingual Training of Crosslingual Word Embeddings

Publisher: Association for Computational Linguistics

Date: 2017

DOI: 10.18653/V1/E17-1084

Learning From Failure: Data Capture in an Australian Aboriginal Community

Publisher: Association for Computational Linguistics

Date: 2022

DOI: 10.18653/V1/2022.ACL-LONG.342

Natural Language Processing and Linguistic Fieldwork

Publisher: MIT Press - Journals

Date: 09-2009

DOI: 10.1162/COLI.35.3.469

Enabling Interactive Transcription in an Indigenous Community

Publisher: International Committee on Computational Linguistics

Date: 2020

DOI: 10.18653/V1/2020.COLING-MAIN.303

Cross-Lingual Word Embeddings for Low-Resource Language Modeling

Publisher: Association for Computational Linguistics

Date: 2017

DOI: 10.18653/V1/E17-1088

University Of Melbourne

Location: Australia

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Charles Darwin University

Location: Australia

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Discovery Projects - Grant ID: DP0770931

Start Date: 2008

End Date: 12-2010

Amount: $325,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP190101983

Start Date: 05-2019

End Date: 06-2024

Amount: $322,500.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0567353

Start Date: 12-2005

End Date: 12-2006

Amount: $98,035.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP0988242

Start Date: 2009

End Date: 12-2011

Amount: $176,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP210100228

Start Date: 2021

End Date: 12-2024

Amount: $366,505.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP120101712

Start Date: 02-2012

End Date: 12-2015

Amount: $123,000.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0453247

Start Date: 04-2004

End Date: 04-2005

Amount: $205,800.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0560711

Start Date: 03-2005

End Date: 03-2006

Amount: $325,873.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0346848

Start Date: 2002

End Date: 12-2002

Amount: $268,000.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE220100010

Start Date: 07-2022

End Date: 06-2024

Amount: $620,000.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE110100142

Start Date: 06-2011

End Date: 12-2011

Amount: $238,000.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0354513

Start Date: 12-2003

End Date: 12-2004

Amount: $20,000.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0354738

Start Date: 01-2004

End Date: 12-2003

Amount: $10,000.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100211

Start Date: 07-2010

End Date: 06-2015

Amount: $650,000.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0354596

Start Date: 01-2004

End Date: 11-2004

Amount: $20,000.00

Funder: Australian Research Council

Research Networks - Grant ID: RN0460284

Start Date: 12-2004

End Date: 12-2010

Amount: $2,000,000.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0354693

Start Date: 2004

End Date: 12-2004

Amount: $10,000.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0354848

Start Date: 03-2004

End Date: 12-2004

Amount: $20,000.00

Funder: Australian Research Council