Preparing Acoustic Pitch Data for Computational Analysis and Presentation

Abstract

Pitch plays an important role in many linguistic systems. It is the primary set of features which determine vowel quality distinctions as well as forming the basis for intonation and contrastive tone systems. Unfortunately, much of the literature has relied on approaches to presenting and analysing pitch data that can result in a lack of data transparency, reproducibility, and analytical robustness. These issues are easily solved through the selection of a more appropriate scale for pitch values. This study presents the issues with using raw pitch data as Hertz values some historical efforts to resolve these issues, and two more appropriate solutions than some of the more widely used systems, with a way to easily calculate these alternative systems in a short Python script.
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Adding Standardized Transcriptions to Panoan and Tacanan Languages in the Intercontinental Dictionary Series

In this study, we illustrate how standardized phonetic transcriptions can be added to the data for Panoan and Tacanan languages provided by the Intercontinental Dictionary Series. The result is presented as a new dataset that keeps reference to the original data and adds phonetic transcriptions for each word form in Panoan languages, Tacanan languages, as well as Spanish and Portuguese.

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Generating Phonological Feature Vectors with SoundVectors and CLTS

The recently published Python library soundvectors offers a simple and robust method to derive phonological feature vectors for any valid IPA sound via its canonical description. It is designed to interact neatly with the Cross-Linguistic Transcription Systems reference catalog (CLTS), which dynamically parses valid strings in phonetic transcription to describe speech sounds. This study illustrates how both systems can be used together to generate phonological feature vectors for all kinds of sounds without relying on a previously defined lookup table. Additionally, it compares the generated feature vectors with those obtained from two other prominent databases, PanPhon and PHOIBLE, showing how those systems can be accessed from the CLTS data via its Python API pyclts.

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Converting an Artificial Proto-Language into Data for Testing Computational Approaches in Historical Linguistics

This small study shows how data for an artificially created language that was supposed to reflect features of “proto-languages”, predating modern languages by several thousand years, can be used in testing computational approaches in historical linguistics. In order to do so,  computational workflow is described that retrieves the data automatically, creating a comparative wordlist compatible in format with software tools for historical linguistics, and then uses a baseline method for automatic cognate detection to compare an artificial language against a sample of Indo-European languages.  The results show that artificial languages might help to fill a gap in testing that has so far been ignored in the literature.

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An Extended Concept List of Vietnamese

As part of our ongoing endeavour to expand the possible mappings in Concepticon, I introduce an extended concept list of Vietnamese based on the Intercontinental Dictionary Series (IDS). The list includes elicitation glosses for 1,310 concepts that can be used as a reference to add more data or for comparative analyses. Here, I present the creation of the list and its content.

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Implementing Fuzzy Spelling Search in Dictionaries of Under-Described Languages Lacking Standard Orthographies

Non-standard orthographies are common in the world of under-described language documentation. Whether they are semi-conventionalised community spellings, orthographies partially adopted from missionary works, or hastily transcribed texts representing as-yet uncertain phonologies, there is a need to be able to work through lexical data in a way which can accommodate and respond to such non-standard transcriptions. Here, a few options are considered, with a solution for fuzzy string matching based on attested variations is presented.

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Representing the Database of Semantic Shifts by Zalizniak et al. from 2024 in Cross-Linguistic Data Formats

In this brief study, we show how the Database of Semantic Shifts, a large resource on semantic change and semantic motivation, can be represented in Cross-Linguistic Data Formats. The representation allows for a convenient quantitative analysis of the numerous annotations on semantic change and semantic motivation and for the integration of the database with additional resources on semantic change and semantic motivation that have been compiled independently in the last years.

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A New Python Library for the Manipulation and Annotation of Linguistic Sequences

The Python package linse (https://pypi.org/project/linse) offers various methods for the manipulation and annotation of sequences. In this short overview, we summarize its major functionalities and provide some information on its background and how we intend to develop it further in the future.

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How to Visualize Colexification Networks in Cytoscape (How to Do X in Linguistics 14)

The ability to visualize data in an intelligible way is an important skill for scientists. In linguistics, especially in lexical semantics, data are often visualized using graphs, i.e., networks. For example, in the web app for the Database of Cross-Linguistic Colexifications (CLICS), we use networks to illustrate that a lexical form refers to two different concepts by connecting the concepts (i.e., nodes) with a line (i.e., edge). When identifying the colexifications between concepts across a large number of languages, the network grows and a tool to visualize multiple data points becomes necessary. Here, I present a tutorial for the first steps to visualize a colexification network with Cytoscape. The tutorial is intended for beginners who want to learn how the tool works and serves as a starting point for further skill development.

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Past and Future of Computer-Assisted Language Comparison in Practice

Our blog “Computer-Assisted Language Comparison in Practice” goes into its seventh year. We reflect on the role the blog played in the past and present and new goals and concrete ideas for the future. The most drastic innovation we initiated is to turn the blog into an open journal, which means that all future and successively also past contributions will be archived in PDF format with digital object identifiers.

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Five Recommendations for Creating Spreadsheets

Through the rapid increase in digital data, the use of tabular formats for data has also increased notably. However, the reusability of data is still an issue due to the lack of transparency in the presentation of data in spreadsheets. In our work with the Concepticon, we sometimes encounter spreadsheets provided by researchers that contain information not transparent to an external audience. Therefore, I offer guidelines on how to format tables with data and provide five concrete recommendations.

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Parsing IPA Transcriptions with CLTS

The Cross-Linguistic Transcription Systems (CLTS, https://clts.clld.org) project serves as a reference catalogue for speech sounds. At the core of the project is a generative method that parses existing IPA transcriptions (or transcriptions in other supported transcription systems) and checks if they conform to the principles and components laid out in the reference catalogue. As a result, Cross-Linguistic Transcription Systems is much more than a simple list of possible speech sounds transcribed in the International Phonetic Alphabet, but a system that allows to generate possible speech sounds and to check if sounds provided in various transcription systems contain problems. This study gives a short overview on the basic ideas that lead to the creation of the database and the parsing method and provides some examples showing how it can be employed in practice.

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Retrieving and Analyzing Taste Colexifications from Lexibank

Colexifications have enjoyed a considerable amount of popularity in the recent years. However, there are still many semantic domains, where not much research on colexification patterns has been carried out so far. Here we show, how the recently published Lexibank repository can be queried to yield colexification data on taste colexifications which can in turn be easily plotted on geographic maps.

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Sequence Manipulation with Orthography Profiles in JavaScript

Orthography profiles allow for the explicit simultaneous segmentation and conversion of sequences from one orthography to another. They play a crucial role in the standardization workflows developed as part of the Cross-Linguistic Data Formats initiative, where they are used to convert original orthographies used for language documentation to a strict version of the International Phonetic Alphabet. Given that the basic algorithm by which orthography profiles can be used to segment and convert sequences across orthographies is very straightforward, it can be easily implemented in JavaScript.
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Creating a CLDF Wordlist from Heath et al.’s Dogon Comparative Wordlist

The Dogon and Bangime Linguistics project (https://dogonlanguages.org) offers a large comparative spreadsheet in which translational equivalents for a huge number of concepts are translated into various Dogon languages.  Due to its enormous size, no attempts have been made so far to integrate the spreadsheet with the lexical resources that were compiled as part of the CLDF initiative in order to populate the Lexibank repository. Here, we report a first attempt to circumvent the problems resulting from the size of the spreadsheet by convert not all but parts of the spreadsheet to CLDF Wordlist standards, which allows us to integrate parts of the data with other resources in Lexibank.

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