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“Learners’ generalization of alternation patterns from ambiguous data” published in AMP2024 Proceedings

We are delighted to announce that the paper “Learners’ generalization of alternation patterns from ambiguous data,” presented at the Annual Meeting on Phonology 2024 (AMP2024), has been published in the conference proceedings. This paper is authored by Bingzi (former member of LDL and current PhD candidate at MIT), Ivy, and Youngah.

The published paper investigates how learners generalize phonological alternation patterns when faced with ambiguous data. It explores whether learners prefer simple or complex rules in their generalizations, shedding light on the biases and mechanisms underlying phonological learning.

The findings indicate that learners tend to favor simpler generalizations, contributing to our understanding of phonological acquisition and cognitive processes involved in language learning. This research represents a significant advancement in the study of phonological learning.

Yu, B., Zheng, S., & Do, Y. (2025). Learners’ Generalization of Alternation Patterns from Ambiguous Data. Proceedings of the Annual Meetings on Phonology, 1(1), Article 1.
open_in_newDOI

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All Lab News Publication

“Preference for Distinct Variants in Learning Sound Correspondences During Dialect Acquisition” published on Language and Speech

We are pleased to announce that Xiaoyu and Youngah’s paper, “Preference for Distinct Variants in Learning Sound Correspondences During Dialect Acquisition,” has been published in the journal Language and Speech.

This research delves into how learners acquire sound correspondences (SCs) in second dialect acquisition. SCs occur when sounds occupy corresponding positions in cognate words of related languages or dialects. While SCs can consist of both similar and distinct variants, the impact of this similarity on learning has been understudied.

In their study, Xiaoyu and Youngah investigated whether the degree of similarity between dialect variants affects SC learning. They employed an artificial language learning experiment where participants learned SCs between Standard Mandarin and “artificial dialects,” using a set of carefully controlled sound contrasts. The degree of similarity between the variants was evaluated using multiple measures, including phonetic and phonological metrics validated by typological evidence.

The findings revealed that while similarity did not impact the learning of simple one-to-one SCs, learners showed a preference for more distinct variants when the SC mapping structure was more complex (i.e., two-to-one or one-to-two mappings). This preference, however, only emerged when the dissimilarity between the variants was sufficiently large to cross a certain threshold.

This study demonstrates that although learners initially display a general lack of sensitivity to similarity differences, a preference for distinct variants emerges when SC mapping structures become more complex and the dissimilarity between variants reaches a critical level. This suggests that when acquiring complex SC patterns, learners seek out more salient cues, leading to an improved ability to differentiate between distinct variants.

Yu, X., & Do, Y. (2025). Preference for Distinct Variants in Learning Sound Correspondences During Dialect Acquisition. Language and Speech. open_in_newDOI

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All Lab News Publication

“Substantive Bias in Artificial Phonology Learning” published on Lang. Linguist. Compass

We are pleased to announce the publication of a review article by Ivy and Youngah, in Language and Linguistics Compass. The article, titled “Substantive Bias in Artificial Phonology Learning,” provides a comprehensive review of the research on substantive bias in phonological learning since the influential 2012 paper by Moreton and Pater.

The review categorizes studies into vowel, consonant, and suprasegmental patterns, highlighting advancements in experimental paradigms, the definition of phonetic naturalness, and the exploration of various phonological phenomena. It emphasizes how subtle methodological choices in experimental designs can affect the results of substantive bias.

Key findings from the review include:

  • Vowel Patterns: Studies on vowel harmony have consistently developed more sophisticated paradigms, highlighting the role of naturalness in learning. The review showed how different training parameters (variable input, iterative learning) influence the effect of substantive bias.
  • Consonant Patterns: Research in this domain has explored various phonological phenomena, including nasalization, voicing, and saltatory alternations, suggesting the importance of considering phonetic precursor strength and the roles of articulatory and perceptual factors when assessing substantive bias effects.
  • Suprasegmental Patterns: Studies on tone and stress patterns have consistently shown a positive effect of substantive bias, differing from segmental patterns. The review suggests that these differences might be related to the learnability of the phonological patterns.

Based on their review, Ivy and Youngah suggest that future research should include:

  1. An examination of the articulatory and perceptual foundations of each phonological pattern
  2. An analysis of the similarities in features, articulation, and perception

The paper not only summarizes current findings but also provides important guidance for future research in phonological learning, particularly in the area of substantive bias.

Zheng, S., & Do, Y. (2025). Substantive Bias in Artificial Phonology Learning. Language and Linguistics Compass, 19(1), e70005. open_in_newDOI

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Lab News

A Voice for the Deaf (HKU Bulletin 2024-11 26.1)

Our Hong Kong Sign Language was covered in the November issue of HKU Bulletin. Read more here:

Kathy, G., & Teri, F. (2024, November). A voice for the deaf. (W. Ho, T. Leung, N. Yu, K. Au, & S. Leung, Eds.) The University of Hong Kong Bulletin26(1), 40–41. Retrieved 2024, from https://www4.hku.hk/pubunit/Bulletin/ebook_2024Nov(26.1)/40-41/.

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Lab News

Learners’ generalization of alternation patterns from ambiguous data @ AMP2024 Rutgers

Ivy recently presented at the Annual Meeting on Phonology 2024 (AMP2024), held from November 1-3 at Rutgers University, on the paper “Learners’ generalization of alternation patterns from ambiguous data”. The paper, written by Bingzi, Ivy and Yonugah, explored the intriguing question of how language learners generalize patterns from ambiguous linguistic data.

The research focuses on the acquisition of alternation patterns, a type of phonological process that involves changes in sound patterns across different word forms. By examining how learners handle ambiguous data, the study sheds light on the cognitive mechanisms underlying phonological learning.

The study highlighted the complex interplay between simplicity and complexity in language acquisition. While learners tend to favor simpler generalizations, they are also capable of acquiring more intricate patterns under specific conditions.

This research has significant implications for our understanding of language development, particularly in the realm of phonology. It contributes to ongoing debates about the role of simplicity and complexity in shaping linguistic knowledge.

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Knowledge Exchange 2023 (Hong Kong Sign Language) Lab News

Hong Kong Sign Language project featured on this month’s HKU Impact

Our Hong Kong Sign Language project is featured in this month’s HKU Impact. Read more here:

https://www.ke.hku.hk/enews/202407/

https://www.ke.hku.hk/story/sign-language

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Lab News

LDL Wins Faculty Knowledge Exchange Award!

We are thrilled to announce that the Language Development Lab (LDL) has been awarded the Faculty Knowledge Exchange Award 2024 for our project titled “The Sound of Silence: A Journey Through Deaf Culture in Hong Kong.” This prestigious award recognizes outstanding research projects that demonstrate exceptional knowledge exchange between the University and the broader community.

Led by Youngah, the LDL team has been working collaboratively with various Deaf community organizations for the past few years. This project aimed to document, preserve, and promote Hong Kong Sign Language (HKSL), while also fostering understanding and inclusivity between the Deaf and hearing communities.

Highlights of the Project’s Impact:

  • Technological Advancement: Developed a HKSL detection model, laying the groundwork for future sign language detection systems.
  • Educational Impact: Fostered new hearing HKSL users through an inclusive HKSL curriculum for hearing students in collaboration with Deaf educators.
  • Social Impact: Created a comprehensive video archive of HKSL signs, combining naturalistic and structured data.
  • Cultural Impact: Supported the production of a documentary film, “Bridge of Signs,” exploring the experiences of the Deaf community and the vital role of HKSL in Deaf identity.
  • Welfare Impact: HKSL-trained volunteers provided essential first aid services at Deaf community sporting events.

Overall, this project has made significant strides in:

  • Documenting HKSL and its unique visual characteristics
  • Preserving HKSL and the intangible Deaf culture
  • Facilitating HKSL learning for hearing students
  • Promoting a sense of ownership and legitimacy of HKSL within the Deaf community
  • Bridging the communication gap between the Deaf and hearing communities

The LDL team is incredibly proud of this achievement and the positive impact this project has had on the Deaf community in Hong Kong. We are committed to continuing our research and outreach efforts to ensure the vibrancy and accessibility of HKSL.

Further details on the project, including its methodology, findings, and beneficiaries, can be found on the KE Awards webpage: Faculty KE Awards

Project team members

(In no particular order)

  • Dr Youngah DO
  • Dr Arthur THOMPSON
  • Dr Robert Marcelo SEVILLA
  • Wing Cheung Aaron CHIK
  • Lihui Frank TAN
  • Shuang ZHENG
  • Chuwen Joanna CHEN
  • Fei Peng Kevin CHEN
  • Pui Ching Rachel CHEN
  • Yu Hei Hannah CHUNG
  • Clarissa KI
  • Xin Olivia LIANG
  • Chui Yin Judy NG
  • Yu On Mavies NGAI
  • Wing Tsun Jeff YIP
Collaboration

The Department of Linguistics at HKU has collaborated with the following parties for this project (in no particular order):

  • Professional Sign Language Training Centre
  • Point Line Mean!
  • HART HAUS
  • Hong Kong Arts Development Council
  • Hong Kong, China Sports Association of the Deaf
  • Hong Kong St John Ambulance
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Lab News Publication

“Tracking phonological regularities” published on Linguistics Vanguard

We are pleased to announce the publication of a new research article titled “Tracking phonological regularities: exploring the influence of learning mode and regularity locus in adult phonological learning” in the journal Linguistics Vanguard. The paper, authored by Xiaoyu, Thomas, Frank, Albert, and Youngah, investigates the ways adults learn phonological patterns in language.

Front matter of the paper "Tracking phonological regularities".

The study focused on the concept of regularity tracking, where learners subconsciously identify and utilize consistent patterns within a language system. The researchers examined how two factors – the learner’s approach (goal-oriented vs. exploratory) and the type of regularity (phonotactics vs. alternation) – influence this process.

Participants were tasked with acquiring vowel harmony rules for forming plurals in an experimental language. Across four conditions, researchers manipulated both the learning approach (whether participants were explicitly given a learning goal) and the type of regularity present in the language (phonotactics governed vowel selection vs. random vowel alternations).

The study’s key finding is that learners exhibited a stronger preference for identifying regularities when they had no explicit learning goal and when the language contained random alternations. This suggests that statistical learning mechanisms – which underlie our ability to unconsciously pick up on patterns – are influenced by the level of uncertainty in the learning environment and the nature of the regularity itself. Learners seem to be more sensitive to avoiding irregularities, particularly when the structure of the language itself is unpredictable. The findings overall suggest that learning strategies and the inherent structure of the language itself play a role in shaping how learners identify and utilize regularities within phonological patterns.

Yu, X., Van Hoey, T., Tan, F., Du, B. & Do, Y. (2024). Tracking phonological regularities: exploring the influence of learning mode and regularity locus in adult phonological learning. Linguistics Vanguard. open_in_newDOI file_download PDF

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Lab News

Presenting at LabPhon19 @ Seoul

Our lab members recently presented in the recent LabPhon19 conference, held from June 27th to 29th, 2024, in Seoul, South Korea. The conference theme was “Where speech sounds meet the architecture of the grammar and beyond.” We presented findings from three distinct areas of investigation: phonetic substance in language learning, tonal representation in Hakka dialects, and the influence of naturalness bias on phonological variation.

Poster Presentations

  • Phonetic substance in alternation learning: This study by Ivy and Youngah investigated how learners acquire grammatical and sound patterns in different domains. The results suggest that while both domains involve structural complexity and naturalness as learning biases, these biases play a stronger role in phonological learning, particularly when the target pattern is complex and unnatural.
  • Syllable-based or Word-based? Representation of tones undergoing merger in Hakka: Ming and Jon explored how native speakers of Wangmudu Hakka represent tones in their minds. Their findings suggest that for tones undergoing merger, speakers rely on word-level representations rather than syllable-level or generalized sandhi rules.
  • The acquisition, contact, and transmission of phonological variation: Xiaoyu, Samuel, Thomas, Bingzi, Frank, Stephen, Wayne and Youngah examined how biases influence phonological variation learning in different language learning contexts. Their results suggest that a bias towards phonetically natural patterns guides learning in acquisition and contact situations, but not necessarily during language transmission.

Corpus Workshop Presentation

  • Attention-LSTM Autoencoder for Phonotactics Learning from Raw Audio Input: Frank and Youngah presented a study on how a neural network model can learn phonotactic knowledge from raw audio data. Their model, designed to mimic early stages of infant language learning, successfully captured the influence of surrounding sounds on the pronunciation of stops following a sibilant fricative in English.
Frank, Xiaoyu, Ivy, Youngah, Jon and Ming enjoying a meal in Seoul.
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Lab News Publication

“Vividness of Mandarin ABB Words”: LangCog

The latest LDL research article titled “What ratings and corpus data reveal about the vividness of Mandarin ABB words” has been published in the journal Language and Cognition. This research was conducted by members of our laboratory, Thomas (currently at KU Leuven), Xiaoyu, Youngah, in collaboration with PAN Tung-le from National Taiwan University.

The journal article.

The goal of this study was to understand the vividness of Mandarin ABB words. ABB words are a type of phrasal compound in Mandarin, consisting of a prosaic syllable A and a reduplicated BB part, resulting in a vivid phrasal compound.

The researchers collected subjective ratings regarding familiarity, iconicity, imagery/imageability, concreteness, sensory experience rating (SER), valence, and arousal for Mandarin ABB words. They contrasted these ratings with two other sets of prosaic word ratings to understand the distinctive role of variables that characterize ABB words.

The findings revealed that the variable that characterizes ABB items consistently throughout these case studies is their high score for imageability, showing that they are indeed rightfully characterized as vivid. The study also demonstrated the importance of contrasting rating data with other comparable datasets of a different phenomenon or data about the same phenomenon compiled in an ontologically different manner.

Van Hoey, T., Yu, X., Pan, T.-L., & Do, Y. (2024). What ratings and corpus data reveal about the vividness of Mandarin ABB words. Language and Cognition, 1–23. open_in_newDOI