Intraspeaker Priming across the New Zealand English Short Front Vowel Shift

A growing body of research in psycholinguistics, corpus linguistics, and sociolinguistics shows that we have a strong tendency to repeat linguistic material that we have recently produced, seen, or heard. The present paper investigates whether priming effects manifest in continuous phonetic variation the way it has been reported in phonological, morphological, and syntactic variation. We analyzed nearly 60,000 tokens of vowels involved in the New Zealand English short front vowel shift (SFVS), a change in progress in which trap/dress move in the opposite direction to kit, from a topic-controlled corpus of monologues (166 speakers), to test for effects that are characteristic of priming phenomena: repetition, decay, and lexical boost. Our analysis found evidence for all three effects. Tokens that were relatively high and front tended to be followed by tokens that were also high and front; the repetition effect weakened with greater time between the prime and target; and the repetition effect was stronger if the prime and target belonged to (different tokens of) the same word. Contrary to our expectations, however, the cross-vowel effects suggest that the repetition effect responded not to the direction of vowel changes within the SFVS, but rather the peripherality of the tokens. We also found an interaction between priming behavior and gender, with stronger repetition effects among men than women. While these findings both indicate that priming manifests in continuous phonetic variation and provide further evidence that priming is among the factors providing structure to intraspeaker variation, they also challenge unitary accounts of priming phenomena.

Structure, Chronology, and Local Social Meaning of a Supra-Local Vowel Shift: Emergence of the Low-Back-Merger Shift in New England

The Low-Back-Merger Shift (LBMS) is a major North American vowel chain shift spreading across many disparate dialect regions. In this field-based study, we examine the speech of fifty-nine White Western Massachusetts speakers, aged 18–89. Using diagnostics in Becker (2019) and Boberg (2019b), we find the LBMS emerging at the expense of the Northern Cities Shift (Labov, Yaeger, & Steiner, 1972) and traditional New England features (Boberg, 2001; Kurath, 1939; Nagy & Roberts, 2004). In Becker's LBMS model (2019:9), the low-back merger (lot-thought) triggers front-vowel shifts. Our results suggest that local social meaning can sometimes override this chronology such that the front-vowel shifts occur before the low-back merger, even as the overall configuration comes to match Becker's predictions. Sociosymbolic meaning associated with the older New England system has led to a different temporal ordering of LBMS components, thus providing new theoretical and empirical insights into the mechanisms by which supralocal patterns are adopted.

Advances in Completely Automated Vowel Analysis for Sociophonetics: Using End-to-End Speech Recognition Systems With DARLA

In recent decades, computational approaches to sociophonetic vowel analysis have been steadily increasing, and sociolinguists now frequently use semi-automated systems for phonetic alignment and vowel formant extraction, including FAVE (Forced Alignment and Vowel Extraction, Rosenfelder et al., 2011; Evanini et al., Proceedings of Interspeech, 2009), Penn Aligner (Yuan and Liberman, J. Acoust. Soc. America, 2008, 123, 3878), and DARLA (Dartmouth Linguistic Automation), (Reddy and Stanford, DARLA Dartmouth Linguistic Automation: Online Tools for Linguistic Research, 2015a). Yet these systems still have a major bottleneck: manual transcription. For most modern sociolinguistic vowel alignment and formant extraction, researchers must first create manual transcriptions. This human step is painstaking, time-consuming, and resource intensive. If this manual step could be replaced with completely automated methods, sociolinguists could potentially tap into vast datasets that have previously been unexplored, including legacy recordings that are underutilized due to lack of transcriptions. Moreover, if sociolinguists could quickly and accurately extract phonetic information from the millions of hours of new audio content posted on the Internet every day, a virtual ocean of speech from newly created podcasts, videos, live-streams, and other audio content would now inform research. How close are the current technological tools to achieving such groundbreaking changes for sociolinguistics? Prior work (Reddy et al., Proceedings of the North American Association for Computational Linguistics 2015 Conference, 2015b, 71–75) showed that an HMM-based Automated Speech Recognition system, trained with CMU Sphinx (Lamere et al., 2003), was accurate enough for DARLA to uncover evidence of the US Southern Vowel Shift without any human transcription. Even so, because that automatic speech recognition (ASR) system relied on a small training set, it produced numerous transcription errors. Six years have passed since that study, and since that time numerous end-to-end automatic speech recognition (ASR) algorithms have shown considerable improvement in transcription quality. One example of such a system is the RNN/CTC-based DeepSpeech from Mozilla (Hannun et al., 2014). (RNN stands for recurrent neural networks, the learning mechanism for DeepSpeech. CTC stands for connectionist temporal classification, the mechanism to merge phones into words). The present paper combines DeepSpeech with DARLA to push the technological envelope and determine how well contemporary ASR systems can perform in completely automated vowel analyses with sociolinguistic goals. Specifically, we used these techniques on audio recordings from 352 North American English speakers in the International Dialects of English Archive (IDEA1), extracting 88,500 tokens of vowels in stressed position from spontaneous, free speech passages. With this large dataset we conducted acoustic sociophonetic analyses of the Southern Vowel Shift and the Northern Cities Chain Shift in the North American IDEA speakers. We compared the results using three different sources of transcriptions: 1) IDEA’s manual transcriptions as the baseline “ground truth”, 2) the ASR built on CMU Sphinx used by Reddy et al. (Proceedings of the North American Association for Computational Linguistics 2015 Conference, 2015b, 71–75), and 3) the latest publicly available Mozilla DeepSpeech system. We input these three different transcriptions to DARLA, which automatically aligned and extracted the vowel formants from the 352 IDEA speakers. Our quantitative results show that newer ASR systems like DeepSpeech show considerable promise for sociolinguistic applications like DARLA. We found that DeepSpeech’s automated transcriptions had significantly fewer character error rates than those from the prior Sphinx system (from 46 to 35%). When we performed the sociolinguistic analysis of the extracted vowel formants from DARLA, we found that the automated transcriptions from DeepSpeech matched the results from the ground truth for the Southern Vowel Shift (SVS): five vowels showed a shift in both transcriptions, and two vowels didn’t show a shift in either transcription. The Northern Cities Shift (NCS) was more difficult to detect, but ground truth and DeepSpeech matched for four vowels: One of the vowels showed a clear shift, and three showed no shift in either transcription. Our study therefore shows how technology has made progress toward greater automation in vowel sociophonetics, while also showing what remains to be done. Our statistical modeling provides a quantified view of both the abilities and the limitations of a completely “hands-free” analysis of vowel shifts in a large dataset. Naturally, when comparing a completely automated system against a semi-automated system involving human manual work, there will always be a tradeoff between accuracy on the one hand versus speed and replicability on the other hand [Kendall and Joseph, Towards best practices in sociophonetics (with Marianna DiPaolo), 2014]. The amount of “noise” that can be tolerated for a given study will depend on the particular research goals and researchers’ preferences. Nonetheless, our study shows that, for certain large-scale applications and research goals, a completely automated approach using publicly available ASR can produce meaningful sociolinguistic results across large datasets, and these results can be generated quickly, efficiently, and with full replicability.

Blame the Printing Press

This chapter focuses on the role of the printing press in the standardization of the English language. A few centuries after the Norman conquest, by the end of the 1300s, English was again a written language. However, there was no agreement on the correct way to write or spell to use as a guide. Some standards started to emerge after the Court of Chancery switched to English in about 1430. This loose, emerging standard came to be known as Chancery English. Then, in 1476, a merchant named William Caxton brought an amazing new invention back to England from the continent: the printing press. This happened to take place during the middle of a major shift in English pronunciation. From the 14th century to the 17th century, the vowel system of English underwent a massive reorganization called the Great Vowel Shift. By the time the Great Vowel Shift had spread through most of the country in spoken language, the writing system, aided by the printing press, had solidified into a standard that was taught, propagated, and reinforced constantly.

ENGLISH PRONUNCIATION DIVERSITY PRODUCED BY INDONESIAN COVER-SINGERS: A CASE STUDY ON THE YOUTUBE CHANNEL

This study focuses on the pronunciation changes of the Indonesian cover-singers on YouTube. It is qualitative research by using documentation technique. There were three subjects of this study namely RM with song “Memories”, AH with song “Thank You Next”, and HD with song “Comethru”. At the first singer’s pronunciation, there were 26 mispronounced words and she did consonant deletion, vowel shift, vowel coalescence, consonant neutralization, consonant insertion, and metathesis. At the second singer’s pronunciation, there were 17 mispronounced words and she did consonant deletion, vowel shift, consonant neutralization, consonant insertion, assimilation, and diphthongization. At the third singer’s pronunciation, there were 12 mispronounced words and she did consonant deletion, consonant neutralization, vowel shift, vowel coalescence, and consonant insertion. These pronunciation changes occur because of the distinction between the phonological system of English and Bahasa Indonesia , and the Indonesian cover-singers still rely on the word’s spelling rather than phonetic sound. Regardless of these two reasons, there are also several similarities in the phonological system between English and Bahasa Indonesia, but the Indonesian cover-singers still perform the pronunciation changes.

The role of corrective feedback and lexical guidance in perceptual learning of a novel L2 accent in dialogue

Perceptual learning of novel accents is a critical skill for second-language speech perception, but little is known about the mechanisms that facilitate perceptual learning in communicative contexts. To study perceptual learning in an interactive dialogue setting while maintaining experimental control of the phonetic input, we employed an innovative experimental method incorporating prerecorded speech into a naturalistic conversation. Using both computer-based and face-to-face dialogue settings, we investigated the effect of two types of learning mechanisms in interaction: explicit corrective feedback and implicit lexical guidance. Dutch participants played an information-gap game featuring minimal pairs with an accented English speaker whose /ε/ pronunciations were shifted to /ɪ/. Evidence for the vowel shift came either from corrective feedback about participants’ perceptual mistakes or from onscreen lexical information that constrained their interpretation of the interlocutor’s words. Corrective feedback explicitly contrasting the minimal pairs was more effective than generic feedback. Additionally, both receiving lexical guidance and exhibiting more uptake for the vowel shift improved listeners’ subsequent online processing of accented words. Comparable learning effects were found in both the computer-based and face-to-face interactions, showing that our results can be generalized to a more naturalistic learning context than traditional computer-based perception training programs.

Local Meanings for Supralocal Change

While the retraction of trap is found throughout the American West, it is primarily associated with California and supposed Californian values in both the popular media and the ears of Californian listeners. This study investigates the local construction of meaning for a supralocal sound change by examining perceptions of trap backing in Kansas, a locale that has also undergone front lax vowel retraction. Thirty-five college students heard matched-guise stimuli differing only by trap F2, guessed speakers’ regional origin, and rated speakers on 14 affective scales. Listeners associated trap backing with California (despite local participation in the sound shift) and general prestige. The authors suggest that this association with general prestige may help to explain the presence of this vowel shift in Kansas despite considerable ideological differences with California. They argue that these results highlight the interaction between local construction of meaning and broader national discourses for a sound change: while stereotypical associations with a sound change can spread rapidly through means like popular media, stance and identity associations are constructed at the local level.

LANGUAGE CHANGES, LESSONS OF COVID-19 AND CORONEOLOGISMS

Worldwide, the changes are either viewed positively as those updating languages or negatively as those deteriorating them. With English widely recognized as an international language, a lingua franca, numerous governmental and non-governmental organizations make it their business to keep the language understandable, at the same time preserving and introducing a variety of meanings and words when dealing with lexis. Changes in grammar (preference for gerunds instead of infinitives, for example) and pronunciation can take longer to be noticed as they happen over a longer period of time (the Great Vowel Shift). Currently, lexical changes get covered in dictionaries with little delay and are easy to track in online versions. Annually, 800-1,000 newly coined words or added meanings push way into English dictionaries. Approximately five times more are coined each year but fail to get in wide use and meet the acceptance criteria of lexicographers. Up to 2019, most lexical innovations were focused on technological breakthroughs. However, in 2020 medicine gained unprecedented attention due to the pandemic, initially pinpointed in Wuhan, China, and later spread all over the world � all the continents are currently exposed to COVID-19. Therefore, it has been of little surprise when in the end of 2020 most of the year words by English dictionaries were about COVID-19, which has irrevocably changed lifestyles and reality. The purpose of the article is to trace lexical changes caused by the coronavirus outbreak and analyse newly-coined lexemes. The following methods were used: linguistic analysis, observation, mathematical calculations. Thus, the purpose of our article is to trace lexical changes caused by the coronavirus outbreak and analyse newlycoined lexemes. Due to the Internet and a significant influence of social media, newly coined words and phrases get swiftly spread globally, some of them originating from hashtags. Analyzing neologisms coined in the pandemic, it is evident that their main aim is to cover new realities such as upperwear, Zumping (Zoom+dumping), etc. It is statistically proven that covid, coron (coronavirus) and quaran (qurantine) are the three most frequent stems. The pandemic-related neologisms are mostly closed compound nouns (covidiot, coronarave). Still spaced ones are often used as well (corona boner, corona bae). Taking into account a boom of coronelogisms worldwide, the Ukrainian language borrowed some either as loan translated (coronapocalypse � ���������������) or transliterated (covidiot � ������). At the same time, some widely used neologisms got translated using Ukrainian stems and affixes (������������, ������, ������������, �����������). Lexical changes, influenced by the pandemic and currently observed in English and Ukrainian, evolve rapidly and they have not come to an end.

(Divergent) Participation in the California Vowel Shift by Korean Americans in Southern California

This study investigates the participation in the California Vowel Shift by Korean Americans in Los Angeles. Five groups of subjects participated in a picture narrative task: first-, 1.5-, and second-generation Korean Americans, Anglo-Californians, and (non-immigrant) Korean late learners of English. Results showed a clear distinction between early vs. late bilinguals; while the first-generation Korean Americans and the late learners showed apparent signs of Korean influence, the 1.5- and the second-generation Korean Americans participated in most patterns of the California Vowel Shift. However, divergence from the Anglo-Californians was observed in early bilinguals’ speech. Similar to the late bilinguals, the 1.5-generation speakers did not systematically distinguish prenasal and non-prenasal /æ/. The second-generation speakers demonstrated a split-/æ/ system, but it was less pronounced than for the Anglo-Californians. These findings suggest that age of arrival has a strong effect on immigrant minority speakers’ participation in local sound change. In the case of the second-generation Korean Americans, certain patterns of the California Vowel Shift were even more pronounced than for the Anglo-Californians (i.e., /ɪ/-lowering, /ɑ/-/ɔ/ merger, /ʊ/- and /ʌ/-fronting). Moreover, the entire vowel space of the second-generation Korean Americans, especially female speakers, was more fronted than that of the Anglo-Californians. These findings suggest that second-generation Korean Americans may be in a more advanced stage of the California Vowel Shift than Anglo-Californians or the California Vowel Shift is on a different trajectory for these speakers. Possible explanations in relation to second-generation Korean Americans’ intersecting gender, ethnic, and racial identities, and suggestions for future research are discussed.