arXiv subjects

Steven Bird

Publications and source records attributed to Steven Bird.

At least 19 recordsLinked to original sources

arXiv2025

Big AI is accelerating the metacrisis: What can we do?

The world is in the grip of ecological, meaning, and language crises that are converging into a metacrisis. Big AI is accelerating them all. LLM engineering sits at the core. Despite the public good motives of language engineers and the promise of LLMs, this work is being leveraged to create unprecedented wealth and power for a handful of individuals and corporations while causing existential harm to life on earth. As a profession, we urgently need to come together to explore alternatives and to design a life-affirming future for our field of natural language processing that is centered on human flourishing on a living planet.

cs.CL↗

arXiv2021

Spoken Term Detection Methods for Sparse Transcription in Very Low-resource Settings

We investigate the efficiency of two very different spoken term detection approaches for transcription when the available data is insufficient to train a robust ASR system. This work is grounded in very low-resource language documentation scenario where only few minutes of recording have been transcribed for a given language so far.Experiments on two oral languages show that a pretrained universal phone recognizer, fine-tuned with only a few minutes of target language speech, can be used for spoken term detection with a better overall performance than a dynamic time warping approach. In addition, we show that representing phoneme recognition ambiguity in a graph structure can further boost the recall while maintaining high precision in the low resource spoken term detection task.

cs.CL↗

arXiv2020

Enabling Interactive Transcription in an Indigenous Community

We propose a novel transcription workflow which combines spoken term detection and human-in-the-loop, together with a pilot experiment. This work is grounded in an almost zero-resource scenario where only a few terms have so far been identified, involving two endangered languages. We show that in the early stages of transcription, when the available data is insufficient to train a robust ASR system, it is possible to take advantage of the transcription of a small number of isolated words in order to bootstrap the transcription of a speech collection.

cs.CL↗

arXiv2020

Bootstrapping Techniques for Polysynthetic Morphological Analysis

Polysynthetic languages have exceptionally large and sparse vocabularies, thanks to the number of morpheme slots and combinations in a word. This complexity, together with a general scarcity of written data, poses a challenge to the development of natural language technologies. To address this challenge, we offer linguistically-informed approaches for bootstrapping a neural morphological analyzer, and demonstrate its application to Kunwinjku, a polysynthetic Australian language. We generate data from a finite state transducer to train an encoder-decoder model. We improve the model by "hallucinating" missing linguistic structure into the training data, and by resampling from a Zipf distribution to simulate a more natural distribution of morphemes. The best model accounts for all instances of reduplication in the test set and achieves an accuracy of 94.7% overall, a 10 percentage point improvement over the FST baseline. This process demonstrates the feasibility of bootstrapping a neural morph analyzer from minimal resources.

cs.CL↗

arXiv2016

Learning Crosslingual Word Embeddings without Bilingual Corpora

Crosslingual word embeddings represent lexical items from different languages in the same vector space, enabling transfer of NLP tools. However, previous attempts had expensive resource requirements, difficulty incorporating monolingual data or were unable to handle polysemy. We address these drawbacks in our method which takes advantage of a high coverage dictionary in an EM style training algorithm over monolingual corpora in two languages. Our model achieves state-of-the-art performance on bilingual lexicon induction task exceeding models using large bilingual corpora, and competitive results on the monolingual word similarity and cross-lingual document classification task.

cs.CL↗

arXiv2003

Extending Dublin Core Metadata to Support the Description and Discovery of Language Resources

As language data and associated technologies proliferate and as the language resources community expands, it is becoming increasingly difficult to locate and reuse existing resources. Are there any lexical resources for such-and-such a language? What tool works with transcripts in this particular format? What is a good format to use for linguistic data of this type? Questions like these dominate many mailing lists, since web search engines are an unreliable way to find language resources. This paper reports on a new digital infrastructure for discovering language resources being developed by the Open Language Archives Community (OLAC). At the core of OLAC is its metadata format, which is designed to facilitate description and discovery of all kinds of language resources, including data, tools, or advice. The paper describes OLAC metadata, its relationship to Dublin Core metadata, and its dissemination using the metadata harvesting protocol of the Open Archives Initiative.

cs.CL↗

arXiv2003

A Grid Based Architecture for High-Performance NLP

We describe the design and early implementation of an extensible, component-based software architecture for natural language engineering applications which interfaces with high performance distributed computing services. The architecture leverages existing linguistic resource description and discovery mechanisms based on metadata descriptions, combining these in a compatible fashion with other software definition abstractions. Within this architecture, application design is highly flexible, allowing disparate components to be combined to suit the overall application functionality, and formally described independently of processing concerns. An application specification language provides abstraction from the programming environment and allows ease of interface with high performance computational grids via a broker.

cs.DC↗

arXiv2003

The Open Language Archives Community: An infrastructure for distributed archiving of language resources

New ways of documenting and describing language via electronic media coupled with new ways of distributing the results via the World-Wide Web offer a degree of access to language resources that is unparalleled in history. At the same time, the proliferation of approaches to using these new technologies is causing serious problems relating to resource discovery and resource creation. This article describes the infrastructure that the Open Language Archives Community (OLAC) has built in order to address these problems. Its technical and usage infrastructures address problems of resource discovery by constructing a single virtual library of distributed resources. Its governance infrastructure addresses problems of resource creation by providing a mechanism through which the language-resource community can express its consensus on recommended best practices.

cs.CL↗

arXiv2003

Grid-Enabling Natural Language Engineering By Stealth

We describe a proposal for an extensible, component-based software architecture for natural language engineering applications. Our model leverages existing linguistic resource description and discovery mechanisms based on extended Dublin Core metadata. In addition, the application design is flexible, allowing disparate components to be combined to suit the overall application functionality. An application specification language provides abstraction from the programming environment and allows ease of interface with computational grids via a broker.

cs.DC↗

arXiv2003

Building an Open Language Archives Community on the OAI Foundation

The Open Language Archives Community (OLAC) is an international partnership of institutions and individuals 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 individuals 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. To address the first, we have developed an extensible application profile for language resource metadata. To address the second, we have implemented Vida (the virtual data provider) and Viser (the virtual service provider), which permit community members to provide data and services without having to implement the OAI protocol. These solutions are generic and could be adopted by other specialized subcommunities.

cs.CL↗

arXiv2002

NLTK: The Natural Language Toolkit

NLTK, the Natural Language Toolkit, is a suite of open source program modules, tutorials and problem sets, providing ready-to-use computational linguistics courseware. NLTK covers symbolic and statistical natural language processing, and is interfaced to annotated corpora. Students augment and replace existing components, learn structured programming by example, and manipulate sophisticated models from the outset.

cs.CL↗

arXiv2002

Phonology

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 will present the fundamentals of descriptive phonology along with a brief overview of computational phonology.

cs.CL↗

arXiv2002

Querying Databases of Annotated Speech

Annotated speech corpora are databases consisting of signal data along with time-aligned symbolic `transcriptions'. Such databases are typically multidimensional, heterogeneous and dynamic. These properties present a number of tough challenges for representation and query. The temporal nature of the data adds an additional layer of complexity. This paper presents and harmonises two independent efforts to model annotated speech databases, one at Macquarie University and one at the University of Pennsylvania. Various query languages are described, along with illustrative applications to a variety of analytical problems. The research reported here forms a part of several ongoing projects to develop platform-independent open-source tools for creating, browsing, searching, querying and transforming linguistic databases, and to disseminate large linguistic databases over the internet.

cs.CL↗

arXiv2002

Seven Dimensions of Portability for Language Documentation and Description

The process of documenting and describing the world's languages is undergoing radical transformation with the rapid uptake of new digital technologies for capture, storage, annotation and dissemination. However, uncritical adoption of new tools and technologies is leading to resources that are difficult to reuse and which are less portable than the conventional printed resources they replace. We begin by reviewing current uses of software tools and digital technologies for language documentation and description. This sheds light on how digital language documentation and description are created and managed, leading to an analysis of seven portability problems under the following headings: content, format, discovery, access, citation, preservation and rights. After characterizing each problem we provide a series of value statements, and this provides the framework for a broad range of best practice recommendations.

cs.CL↗

arXiv2002

Annotation Graphs and Servers and Multi-Modal Resources: Infrastructure for Interdisciplinary Education, Research and Development

Annotation graphs and annotation servers offer infrastructure to support the analysis of human language resources in the form of time-series data such as text, audio and video. This paper outlines areas of common need among empirical linguists and computational linguists. After reviewing examples of data and tools used or under development for each of several areas, it proposes a common framework for future tool development, data annotation and resource sharing based upon annotation graphs and servers.

cs.CL↗

arXiv2002

Computational Phonology

Phonology, as it is practiced, is deeply computational. Phonological analysis is data-intensive and the resulting models are nothing other than specialized data structures and algorithms. In the past, phonological computation - managing data and developing analyses - was done manually with pencil and paper. Increasingly, with the proliferation of affordable computers, IPA fonts and drawing software, phonologists are seeking to move their computation work online. Computational Phonology provides the theoretical and technological framework for this migration, building on methodologies and tools from computational linguistics. This piece consists of an apology for computational phonology, a history, and an overview of current research.

cs.CL↗

arXiv2002

Models and Tools for Collaborative Annotation

The Annotation Graph Toolkit (AGTK) is a collection of software which facilitates development of linguistic annotation tools. AGTK provides a database interface which allows applications to use a database server for persistent storage. This paper discusses various modes of collaborative annotation and how they can be supported with tools built using AGTK and its database interface. We describe the relational database schema and API, and describe a version of the TableTrans tool which supports collaborative annotation. The remainder of the paper discusses a high-level query language for annotation graphs, along with optimizations, in support of expressive and efficient access to the annotations held on a large central server. The paper demonstrates that it is straightforward to support a variety of different levels of collaborative annotation with existing AGTK-based tools, with a minimum of additional programming effort.

cs.CL↗

arXiv2002

Creating Annotation Tools with the Annotation Graph Toolkit

The Annotation Graph Toolkit is a collection of software supporting the development of annotation tools based on the annotation graph model. The toolkit includes application programming interfaces for manipulating annotation graph data and for importing data from other formats. There are interfaces for the scripting languages Tcl and Python, a database interface, specialized graphical user interfaces for a variety of annotation tasks, and several sample applications. This paper describes all the toolkit components for the benefit of would-be application developers.

cs.CL↗