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1. Individual Chunking Ability Predicts Efficient or Shallow L2 Processing: Eye-Tracking Evidence From Multiword Units in Relative Clauses

   https://doi.org/10.3389/fpsyg.2020.607621  

   Pulido, Manuel F. ( January 2021 , Frontiers in Psychology)

   null (Ed.)

   Behavioral studies on language processing rely on the eye-mind assumption, which states that the time spent looking at text is an index of the time spent processing it. In most cases, relatively shorter reading times are interpreted as evidence of greater processing efficiency. However, previous evidence from L2 research indicates that non-native participants who present fast reading times are not always more efficient readers, but rather shallow parsers. Because earlier studies did not identify a reliable predictor of variability in L2 processing, such uncertainty around the interpretation of reading times introduces a potential confound that undermines the credibility and the conclusions of online measures of processing. The present study proposes that a recently developed modulator of online processing efficiency, namely, chunking ability, may account for the observed variability in L2 online reading performance. L1 English – L2 Spanish learners’ eye movements were analyzed during natural reading. Chunking ability was predictive of overall reading speed. Target relative clauses contained L2 Verb-Noun multiword units, which were manipulated with regards to their L1-L2 congruency. The results indicated that processing of the L1-L2 incongruent units was modulated by an interaction of L2 chunking ability and level of knowledge of multiword units. Critically, the data revealed an inverse U-shaped pattern, with faster reading times in both learners with the highest and the lowest chunking ability scores, suggesting fast integration in the former, and lack of integration in the latter. Additionally, the presence of significant differences between conditions was correlated with individual chunking ability. The findings point at chunking ability as a significant modulator of general L2 processing efficiency, and of cross-language differences in particular, and add clarity to the interpretation of variability in the online reading performance of non-native speakers. 

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2. Eye Movement Traces of Linguistic Knowledge in Native and Non-Native Reading

   https://doi.org/10.1162/opmi_a_00084  

   Berzak, Yevgeni ; Levy, Roger ( January 2023 , Open Mind)

   The detailed study of eye movements in reading has shed considerable light into how language processing unfolds in real time. Yet eye movements in reading remain inadequately studied in non-native (L2) readers, even though much of the world’s population is multilingual. Here we present a detailed analysis of the quantitative functional influences of word length, frequency, and predictability on eye movement measures in reading in a large, linguistically diverse sample of non-native English readers. We find many similar qualitative effects as in L1 readers, but crucially also a proficiency-sensitive “lexicon-context tradeoff”. The most proficient L2 readers’ eye movements approach an L1 pattern, but as L2 proficiency diminishes, readers’ eye movements become less sensitive to a word’s predictability in context and more sensitive to word frequency, which is context-invariant. This tradeoff supports a rational, experience-dependent account of how context-driven expectations are deployed in L2 language processing.

    

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3. PoseASL: An RGBD Dataset of American Sign Language

   https://doi.org/10.17910/b7.1279  

   Huenerfauth, Matt ( January 2021 , Databrary)

   The PoseASL dataset consists of color and depth videos collected from ASL signers at the Linguistic and Assistive Technologies Laboratory under the direction of Matt Huenerfauth, as part of a collaborative research project with researchers at the Rochester Institute of Technology, Boston University, and the University of Pennsylvania. Access: After becoming an authorized user of Databrary, please contact Matt Huenerfauth if you have difficulty accessing this volume. We have collected a new dataset consisting of color and depth videos of fluent American Sign Language signers performing sequences ASL signs and sentences. Given interest among sign-recognition and other computer-vision researchers in red-green-blue-depth (RBGD) video, we release this dataset for use by the research community. In addition to the video files, we share depth data files from a Kinect v2 sensor, as well as additional motion-tracking files produced through post-processing of this data. Organization of the Dataset: The dataset is organized into sub-folders, with codenames such as "P01" or "P16" etc. These codenames refer to specific human signers who were recorded in this dataset. Please note that there was no participant P11 nor P14; those numbers were accidentally skipped during the process of making appointments to collect video stimuli. Task: During the recording session, the participant was met by a member of our research team who was a native ASL signer. No other individuals were present during the data collection session. After signing the informed consent and video release document, participants responded to a demographic questionnaire. Next, the data-collection session consisted of English word stimuli and cartoon videos. The recording session began with showing participants stimuli consisting of slides that displayed English word and photos of items, and participants were asked to produce the sign for each (PDF included in materials subfolder). Next, participants viewed three videos of short animated cartoons, which they were asked to recount in ASL: - Canary Row, Warner Brothers Merrie Melodies 1950 (the 7-minute video divided into seven parts) - Mr. Koumal Flies Like a Bird, Studio Animovaneho Filmu 1969 - Mr. Koumal Battles his Conscience, Studio Animovaneho Filmu 1971 The word list and cartoons were selected as they are identical to the stimuli used in the collection of the Nicaraguan Sign Language video corpora - see: Senghas, A. (1995). Children’s Contribution to the Birth of Nicaraguan Sign Language. Doctoral dissertation, Department of Brain and Cognitive Sciences, MIT. Demographics: All 14 of our participants were fluent ASL signers. As screening, we asked our participants: Did you use ASL at home growing up, or did you attend a school as a very young child where you used ASL? All the participants responded affirmatively to this question. A total of 14 DHH participants were recruited on the Rochester Institute of Technology campus. Participants included 7 men and 7 women, aged 21 to 35 (median = 23.5). All of our participants reported that they began using ASL when they were 5 years old or younger, with 8 reporting ASL use since birth, and 3 others reporting ASL use since age 18 months. Filetypes: *.avi, *_dep.bin: The PoseASL dataset has been captured by using a Kinect 2.0 RGBD camera. The output of this camera system includes multiple channels which include RGB, depth, skeleton joints (25 joints for every video frame), and HD face (1,347 points). The video resolution produced in 1920 x 1080 pixels for the RGB channel and 512 x 424 pixels for the depth channels respectively. Due to limitations in the acceptable filetypes for sharing on Databrary, it was not permitted to share binary *_dep.bin files directly produced by the Kinect v2 camera system on the Databrary platform. If your research requires the original binary *_dep.bin files, then please contact Matt Huenerfauth. *_face.txt, *_HDface.txt, *_skl.txt: To make it easier for future researchers to make use of this dataset, we have also performed some post-processing of the Kinect data. To extract the skeleton coordinates of the RGB videos, we used the Openpose system, which is capable of detecting body, hand, facial, and foot keypoints of multiple people on single images in real time. The output of Openpose includes estimation of 70 keypoints for the face including eyes, eyebrows, nose, mouth and face contour. The software also estimates 21 keypoints for each of the hands (Simon et al, 2017), including 3 keypoints for each finger, as shown in Figure 2. Additionally, there are 25 keypoints estimated for the body pose (and feet) (Cao et al, 2017; Wei et al, 2016). Reporting Bugs or Errors: Please contact Matt Huenerfauth to report any bugs or errors that you identify in the corpus. We appreciate your help in improving the quality of the corpus over time by identifying any errors. Acknowledgement: This material is based upon work supported by the National Science Foundation under award 1749376: "Collaborative Research: Multimethod Investigation of Articulatory and Perceptual Constraints on Natural Language Evolution." 

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4. Do Explicit Instruction and High Variability Phonetic Training Improve Nonnative Speakers’ Mandarin Tone Productions?

   https://doi.org/10.1111/modl.12619  

   WIENER, SETH ; CHAN, MARJORIE K. M. ; ITO, KIWAKO ( January 2020 , The Modern Language Journal)

   This study examines the putative benefits of explicit phonetic instruction, high variability phonetic training, and their effects on adult nonnative speakers’ Mandarin tone productions. Monolingual first language (L1) English speakers (n= 80), intermediate second language (L2) Mandarin learners (n= 40), and L1 Mandarin speakers (n= 40) took part in a multiday Mandarin‐like artificial language learning task. Participants were asked to repeat a syllable–tone combination immediately after hearing it. Half of all participants were exposed to speech from 1 talker (low variability) while the other half heard speech from 4 talkers (high variability). Half of the L1 English participants were given daily explicit instruction on Mandarin tone contours, while the other half were not. Tone accuracy was measured by L1 Mandarin raters (n= 104) who classified productions according to their perceived tonal category. Explicit instruction of tone contours facilitated L1 English participants’ production of rising and falling tone contours. High variability input alone had no main effect on participants’ productions but interacted with explicit instruction to improve participants’ productions of high‐level tone contours. These results motivate an L2 tone production training approach that consists of explicit tone instruction followed by gradual exposure to more variable speech.

    

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5. When event knowledge overrides word order in sentence comprehension: Learning a first language after childhood

   https://doi.org/10.1111/desc.13073  

   Cheng, Qi ; Mayberry, Rachel I. ( January 2021 , Developmental Science)

   Limited language experience in childhood is common among deaf individuals, which prior research has shown to lead to low levels of language processing. Although basic structures such as word order have been found to be resilient to conditions of sparse language input in early life, whether they are robust to conditions of extreme language delay is unknown. The sentence comprehension strategies of post‐childhood, first‐language (L1) learners of American Sign Language (ASL) with at least 9 years of language experience were investigated, in comparison to two control groups of learners with full access to language from birth (deaf native signers and hearing L2 learners who were native English speakers). The results of a sentence‐to‐picture matching experiment show that event knowledge overrides word order for post‐childhood L1 learners, regardless of the animacy of the subject, while both deaf native signers and hearing L2 signers consistently rely on word order to comprehend sentences. Language inaccessibility throughout early childhood impedes the acquisition of even basic word order. Similar to the strategies used by very young children prior to the development of basic sentence structure, post‐childhood L1 learners rely more on context and event knowledge to comprehend sentences. Language experience during childhood is critical to the development of basic sentence structure.

    

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