I'm sharing this here mostly due to the alphabet. The relevant region (Tartessos) would be roughly what's today the western parts of Andalucia, plus the Algarve.

Here are the news in Spanish, for anyone interested.

The number of letters is specially relevant for me - 32 letters. The writing system is a redundant alphabet, where you use different graphemes for the stops, depending on the next vowel; and it was likely made for a language with five vowels, so you had five letters for /p/, five for /t/, five for /k/. Counting the "bare" vowels this yields 20 letters; /m n s r l/ fit well with that phonology, but what about the other seven?

cross-posted from: https://programming.dev/post/15125500

> xkcd \#2942: Fluid Speech > > https://xkcd.com/2942 > > explainxkcd.com for \#2942 > > Alt text: > > Thank you to linguist Gretchen McCulloch for teaching me about phonetic assimilation, and for teaching me that if you stand around in public reading texts from a linguist and murmuring example phrases to yourself, people will eventually ask if you're okay.

> they were taking part in an unusual experiment, which involved tracking their own voices over time. This was done by making 10-minute recordings every few weeks. They would sit in front of a microphone and repeat the same 29 words as they appeared on a computer screen. Food. Coffee. Hid. Airflow.

> One of those changes was the "ou" sound in words such as "flow" and "sew" that shifted towards the front of the vocal tract.

I'm not actually sure what sound change they're describing there. Can anyone explain with examples or IPA?

edit: Cheers for the answers (turns out I misunderstood which part is the vocal tract)

This is not bad

Hi, I'm a casual linguistics nerd (no degrees), speaking Philippine English with heavy American influence.

My accent of English has pre-nasal /æ/ raising and I've caught myself raising it in other places like before /g/.

When I look at English language learning videos (out of curiosity) I have not found anyone mention /æ/ raising in them.

Why is this case?

I'm sharing this mostly as a historical curiosity; Schleicher was genial, but the book is a century and half old, science marches on, so it isn't exactly good source material. Still an enjoyable read if you like Historical Linguistics, as it was one of the first successful attempts to reconstruct a language based on indirect output from its child languages.

Link for the Science research article. The observation that societies without access to softer food kind of avoided labiodentals is old, from 1985, but the research is recent-ish (2019).

What are the terms for language anachronisms?

I had a conversation about a year ago with someone about anachronisms in language. We both felt that there were terms for these things, but could neither recall nor find (via web search) satisfying answers. This came up again recently in a different discussion in a Lemmy community, and it's driving me a little nuts. Help me Linguistics-Wan Kenobi; you're my only hope.

So we have the term "skeumorphism," which refers to oramental anachronism. I may be using "anachronism" incorrectly, but it's the hammer I have. Skeumorphisms, in computers, refer to the graphical representations of things, but not the underlying concepts. There are similar linguistic anachronisms that I feel also have specific labels:

• "disks" which are still in use, but are largely being replaced by solid-state, rectangular SSDs; but most people still call all persistent storage devices "disks."
• "film" to refer to movies, regardless of the media (increasingly digital and having nothing to do with film).
• "rice" to refer to the process of fancifying something, like computer desktops
• "desktops" to refer to computer GUI window managing interfaces
• "files" and "folders" in computers

Are these all the same category of things? Is there a term for them?

Même texte en français ici. I'll copypaste the English version here in case of paywall.

Accents are one of the cherished hallmarks of cultural diversity.

Why AI software ‘softening’ accents is problematic

Published 2024/Jan/11\ by Grégory Miras, Professeur des Universités en didactique des langues, Université de Lorraine

“Why isn’t it a beautiful thing?” a puzzled Sharath Keshava Narayana asked of his AI device masking accents.

Produced by his company, Sanas, the recent technology seeks to “soften” the accents of call centre workers in real-time to allegedly shield them from bias and discrimination. It has sparked widespread interest both in the English-speaking and French-speaking world since it was launched in September 2022.

Far from everyone is convinced of the software’s anti-racist credentials, however. Rather, critics contend it plunges us into a contemporary dystopia where technology is used to erase individuals’ differences, identity markers and cultures.

To understand them, we could do worse than reviewing what constitutes an accent in the first place. How can they be suppressed? And in what ways does ironing them out bends far more than sound waves?

How artificial intelligence can silence an accent

“Accents” can be defined, among others, as a set of oral clues (vowels, consonants, intonation, etc.) that contribute to the more or less conscious elaboration of hypotheses on the identity of individuals (e.g. geographically or socially). An accent can be described as regional or foreign according to different narratives.

With start-up technologies typically akin to black boxes, we have little information about the tools deployed by Sanas to standardise our way of speaking. However, we know most methods aim to at least partially transform the structure of the sound wave in order to bring certain acoustic cues closer to a perceptive criteria. The technology tweaks vowels, consonants along with parameters such as rhythm, intonation or accentuation. At the same time, the technology will be looking to safeguard as many vocal cues as possible to allow for the recognition of the original speaker’s voice, such as with voice cloning, a process that can result in deepfake vocal scams. These technologies make it possible to dissociate what is speech-related from what is voice-related.

The automatic and real-time processing of speech poses technological difficulties, the main one being the quality of the sound signal to be processed. Software developers have succeeded in overcoming them by basing themselves on deep learning, neural networks, as well as large data bases of speech audio files, which make it possible to better manage the uncertainties in the signal.

In the case of foreign languages, Sylvain Detey, Lionel Fontan and Thomas Pellegrini identify some of the issues inherent in the development of these technologies, including that of which standard to use for comparison, or the role that speech audio files can have in determining them.

The myth of the neutral accent

But accent identification is not limited to acoustics alone. Donald L. Rubin has shown that listeners can recreate the impression of a perceived accent simply by associating faces of supposedly different origins with speech. In fact, absent these other cues, speakers are not so good at recognising accents that they do not regularly hear or that they might stereotypically picture, such as German, which many associate with “aggressive” consonants.

The wishful desire to iron out accents to combat prejudice raises the question of what a “neutral” accent is. Rosina Lippi-Green points out that the ideology of the standard language - the idea that there is a way of expressing oneself that is not marked - holds sway over much of society but has no basis in fact. Vijay Ramjattan further links recent collossal efforts to develop accent “reduction” and “suppression” tools with the neoliberal model, under which people are assigned skills and attributes on which they depend. Recent capitalism perceives language as a skill, and therefore the “wrong accent” is said to lead to reduced opportunities.

Intelligibility thus becomes a pretext for blaming individuals for their lack of skills in tasks requiring oral communication according to Janin Roessel. Rather than forcing individuals with “an accent to reduce it”, researchers such as Munro and Derwing have shown that it is possible to train individuals to adapt their aural abilities to phonological variation. What’s more, it’s not up to individuals to change, but for public policies to better protect those who are discriminated against on the basis of their accent - accentism.

Delete or keep, the chicken or the egg?

In the field of sociology, Wayne Brekhus calls on us to pay specific attention to the invisible, weighing up what isn’t marked as much as what is, the “lack of accent” as well as its reverse. This leads us to reconsider the power relations that exist between individuals and the way in which we homogenise the marked: the one who has (according to others) an accent.

So we are led to Catherine Pascal’s question of how emerging technologies can hone our roles as “citizens” rather than “machines”. To “remove an accent” is to value a dominant type of “accent” while neglecting the fact that other co-factors will participate in the perception of this accent as well as the emergence of discrimination. “Removing the accent” does not remove discrimination. On the contrary, the accent gives voice to identity, thus participating in the phenomena of humanisation, group membership and even empathy: the accent is a channel for otherness.

If technologies such AI and deep learning offers us untapped possibilities, they can also lead to a dystopia where dehumanisation overshadows priorities such as the common good or diversity, as spelt out in the UNESCO Universal Declaration on Cultural Diversity. Rather than hiding them, it seems necessary to make recruiters aware of how accents can contribute to customer satisfaction and for politicians to take up this issue.

Research projects such as PROSOPHON at the University of Lorraine (France), which bring together researchers in applied linguistics and work psychology, are aimed at making recruiters more aware of their responsibilities in terms of biais awareness, but also at empowering job applicants “with an accent”. By asking the question “Why isn’t this a beautiful thing?”, companies like SANAS remind us why technologies based on internalized oppressions don’t make people happy at work.