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Xihong's Submission to CCMT 2024: Human-in-the-Loop Data Augmentation for Low-Resource Tibetan-Chinese NMT 20th

Xihong's Submission to CCMT 2024: Human-in-the-Loop Data Aug...

引用

20th China Conference on Machine Translation

作者： Hu, Jiawei Chen, Yincun Zhang, Hanyu Xihong Intelligent Technol Co Ltd Huangshi Hubei Peoples R China

ISBN: (纸本)9789819622917;9789819622924

This paper presents a human-in-the-loop approach to address the challenge of low-resource neural machine translation (NMT), focusing on the Tibetan-Chinese language pair. We emphasize the crucial role of human feedback in both data augmentation and model optimization. First, we construct a large-scale Tibetan-Chinese parallel corpus by iteratively leveraging back-translation and incorporating human evaluation to guide the generation of high-quality synthetic data. Then, we train a multilingual NMT system using a curriculum learning strategy, progressively incorporating the augmented data. Finally, we fine-tune our model with GaLore and SimPO algorithms, directly optimizing it towards human preferences as assessed by professional translators. Experimental results on the CCMT 2024 Tibetan-Chinese translation task demonstrate that our approach significantly improves translation quality, achieving state-of-the-art performance. We provide further analysis and case studies to illustrate the effectiveness of our human-in-the-loop methodology.

关键词： Tibetan-Chinese Translation Curriculum Learning Human-in-the-Loop

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Arabic Dialect Audio Identification Using Wav2Vec2 8th

Arabic Dialect Audio Identification Using Wav2Vec2

引用

8th International Conference on Arabic Language Processing

作者： Khaled, M. Moneb Elnagar, Ashraf Univ Sharjah Dept Comp Sci Sharjah 27272 U Arab Emirates

ISBN: (纸本)9783031804373;9783031804380

There is a broad range of languages around the globe, each of which has a variety of spoken dialects. Dialect refers to a variety in a language's vocabulary, idioms, grammar, and pronunciation. Dialect Identification (DID) is an automatic process to detect to which dialect a speech utterance belongs. Moreover, Arabic Dialect Identification (ADI) is considered one of the most challenging DID tasks since some dialects share many vocabularies, and there is a massive overlap in the linguistic and acoustic features between the countries that belong to the same region. Furthermore, while the work is saturated on DID systems in other languages, the Arabic language still lags behind. Therefore, we present an approach that utilizes transfer learning techniques for classifying both regions and countries. We used a subset of the MGB-5 dataset, and employed Mel-Frequency Cepstral Coefficients (MFCC) as a feature extraction method, then fed the features into the ResNet-LSTM model. However, in this method, we proposed a multi-output approach that combines the classification of regions and countries into one single model, which proved to achieve better results than the single-output approach. After that, we utilized a pre-trained audio model that proved to be highly effective for language-speech tasks, called Wav2Vec2. We used the XLSR variant fine-tuned on the MGB-3 dataset, to train the model on the same small subset and it achieved an accuracy of 93.49% and 93.20% on regions and countries, respectively, which shows the potential of applying state-of-the-art pre-trained audio models on the ADI task.

关键词： Arabic Dialects Audio Identification Dialect Identification Wav2Vec2

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Lan-Bridge's Submission to CCMT 2024 Translation Evaluation Task 20th

Lan-Bridge's Submission to CCMT 2024 Translation Evaluation ...

引用

20th China Conference on Machine Translation

作者： Luo, Min Hu, Gang Wei, Jie Lan Bridge Chengdu Peoples R China

ISBN: (纸本)9789819622917;9789819622924

This paper mainly introduces the basic situation of Lan-Bridge's participation in the CCMT 2024 machine translation evaluation project. In this evaluation, we participate in the bilingual translation projects for three minority languages: Mongolian to Chinese, Tibetan to Chinese, and Uygur to Chinese. We adopt the Transformer model based on the self-attention network as our foundation and train three machine translation models for these three language pairs. The paper primarily discusses the specific methods and experimental details employed by the model, providing an in-depth analysis and discussion of the model performance in the bilingual translation tasks for the three minority languages.

关键词： CCMT 2024 lowsource machine translation transformer

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The Impact of Cognitive, Affective, and Psychomotor Learning Perception on Learning Outcomes in the eXtended Reality Based Nursing Simulation 10th

The Impact of Cognitive, Affective, and Psychomotor Learning...

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10th International Conference of the Immersive Learning Research Network

作者： Jeong, Yuseon Kim, Kukhyeon Ryu, Jeeheon Chonnam Natl Univ Gwangju 61186 South Korea

ISBN: (纸本)9783031804748;9783031804755

This study explores the impact of learner perceptions across the cognitive, affective, and psychomotor domains on educational outcomes using extended reality-based nursing simulation. A cohort of 113 nursing students participated in this research. These students engaged in simulation exercises and concurrently evaluated their experiences from cognitive, affective, and psychomotor perspectives. This research assessed how these perceptions influenced vital learning outcomes, including self-efficacy, focus of attention, learning satisfaction, and SIM-TLX scores. Notably, our results indicate that perceptions within the psychomotor domain significantly enhanced the focus of attention. Conversely, perceptions in the cognitive and affective domains did not significantly impact other learning outcomes. These findings suggest that recognizing and incorporating learners' self-assessed competencies in designing and implementing extended reality-based simulations in nursing education can significantly enhance the educational impact. This approach may lead to improved targeted outcomes by tailoring educational experiences that reflect learners' strengths and needs, thus optimizing overall educational effectiveness.

关键词： XR Nursing Simulation Learning Perception Self-Efficacy Task Load Index Focus of Attention Learning Satisfaction

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The Potential of Virtual Reality for Immersive HCI Education: Insights from an Empirical Study 10th

The Potential of Virtual Reality for Immersive HCI Education...

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10th International Conference of the Immersive Learning Research Network

作者： Shah, Tanmesh Riener, Andreas Tech Hsch Ingolstadt Esplanade 10 D-85049 Ingolstadt Germany

ISBN: (纸本)9783031804748;9783031804755

Virtual Reality (VR) presents a promising avenue for enhancing student engagement and learning outcomes in education. This work aimed to identify key design principles for effective VR learning environments and evaluate VR's impact on student engagement, motivation, and knowledge retention. The research revealed considerable potential for VR-based learning in the STEM field, particularly in the area of human-computer interaction (HCI). This was achieved through a comprehensive approach involving online surveys, expert and student interviews, and mixed-methods VR studies. The results show that memory, attention, relevance, confidence, and satisfaction improve compared to traditional methods described in the Attention, Relevance, Confidence, and Satisfaction (ARCS) model. The Technology Acceptance Model further highlighted VR's high acceptance and usability among students, suggesting its strategic incorporation into educational frameworks. Leveraging VR's immersive capabilities can invigorate student learning experiences, creating dynamic environments that resonate with modern learners through experiential learning and real-world applications. The VR system developed here effectively engages students with a "learning by doing" approach. However, it also highlights ongoing issues, including time-consuming setups, limited user control, and accessibility challenges in VR learning.

关键词： Immersive Learning Concept Memorization Conceptual Understanding Active Participation VR Learning HCI STEM

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Exploring the Influence of Immersive Virtual Reality on science Learning - An Affordance Approach 10th

Exploring the Influence of Immersive Virtual Reality on Scie...

引用

10th International Conference of the Immersive Learning Research Network

作者： Froehlich, Fabian Plass, Jan L. Homer, Bruce D. NYU New York NY 10012 USA CUNY Grad Ctr New York NY 10016 USA

ISBN: (纸本)9783031804748;9783031804755

Research on the effectiveness of immersive VR for science learning has found mixed results when VR learning is compared to traditional learning. While media comparison studies have been criticised for their methodological problems, they provide important information for policy makers as well as for educators. We believe the mixed results were found because many VR learning environments do not take advantage of the unique affordances of VR. We therefore designed Looking Inside Cells (LIC), a set of VR simulations that are interactive, immersive, use spatial features of VR, and take advantage of emotional design. We compared LIC to a slide show of the same content in a quasi-experimental between-subject control group design (N = 63). Outcome variables were recall, comprehension, interest, motivation, and experienced emotions. Results indicate that learners in the VR group scored significantly higher than learners in the control group on some dimensions of the post assessment. The treatment group reported higher levels of positive affect and interest. The results endorse the idea that adopting an affordances approach can enhance the effectiveness of VR in a learning context.

关键词： Immersive VR VR Affordances STEM Learning Affect Media Comparison

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Subject- and Process-Oriented Comparison of Multi-factor Authentication Methods 15th

Subject- and Process-Oriented Comparison of Multi-factor Aut...

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15th International Conference on Subject Oriented Business Process Management

作者： Lawall, Alexander Beenken, Petra IU Int Univ Appl Sci Erfurt Germany

ISBN: (纸本)9783031720406;9783031720413

This paper examines the impact of Authenticator Assurance Levels (AAL) on user efficiency in authentication processes, aiming to balance security and usability. The central research question investigates how AAL levels influence user efficiency, particularly concerning the number of required "keys". Using S-BPM notation, the study offers insights into the authentication landscape through a subject- and process-oriented comparison. Considering how subjects handle authenticators, it's evident that an authenticator app may be preferable to a hardware key in certain contexts, as users are typically vigilant about their smartphones. The analysis concludes that higher AAL levels, like AAL3, offer a more streamlined authentication experience with fewer required "keys", aligning with users' daily interaction patterns and enhancing overall usability. Integrating these findings into cybersecurity practices can enhance multi-factor authentication methods, fostering a more secure and user-centric environment.

关键词： Muli-Factor Authentication S-BPM NIST AAL

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Study on Prosodic Disambiguation of VP/NP Syntactic Structure by Chinese EFL Learners 19th

Study on Prosodic Disambiguation of VP/NP Syntactic Structur...

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19th National Conference on Man-Machine Speech Communication

作者： Guo, Jia Ang, Qiuxiang Liu, Jiachun Zhang, Yuanyuan Nankai Univ Tianjin 300071 Peoples R China

ISBN: (纸本)9789819610440;9789819610457

Under the framework of Language Transfer and Prosodic Learning Interference Hypothesis, this study explores the influence of mother tongue on Chinese EFL learners' L2 English prosodic disambiguation on the basis of Chinese EFL learners' disambiguation in their L1 Chinese. The four parameters, duration, pause (if present), pitch (converted to semitone), and amplitude integral, are extracted. The results indicate (1) duration is the cue that functions efficiently. English natives produce C2 in NP longer than in VP, and this difference is significant. (2) In their mother language, Chinese EFL learners can disambiguate VP/NP ambiguity effectively. To be specific, participants produce both C1 and C2 in VP with longer duration, larger pitch range and greater amplitude integral, and this difference reach the significance level. (3) In their L2 English, Chinese EFL learners, like native English speakers, can effectively utilize duration to achieve the differentiating goal, but their specific performance is different from English natives' in that English natives show significant difference in duration ratio and C2's duration, while L2 learners show the difference in C1, which is partly influenced by their L1 Chinese and can be explained by Prosodic Learning Interference Hypothesis.

关键词： VP/NP syntactic structure Prosodic disambiguation Chinese EFL learners

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Opportunities to Use Arabic YouTube Comments in Text Mining and Masked Language Modeling 8th

Opportunities to Use Arabic YouTube Comments in Text Mining ...

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8th International Conference on Arabic Language Processing

作者： Khenchouch, Mohamed Zeroual, Imad El Kah, Anoual Moulay Ismail Univ L STI T IDMS FST Errachidia Meknes Morocco Sultan Moulay Slimane Univ Polydisciplinary Fac Beni Mellal Morocco

ISBN: (纸本)9783031804373;9783031804380

This study aims to extract meaningful information and explore some well-known Arabic-based transformer models in masked language modeling while investigating the interplay of the minimal length of the sentence and the percentage of masking. To this aim, we have used, for the first time, the opinions expressed in the comments of some trend YouTube channels in Morocco. By controlling the granularity of the input sequences during training, our findings indicate that employing 15 tokens as a minimal value can serve as an effective parameter during the fine-tuning of Arabic masked language models across the 15% and 40% masking rates.

关键词： Transformers Text mining Mask language modeling Natural language processing BERT PLM

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MAOffens: Moroccan Arabic Offensive Language Dataset 8th

MAOffens: Moroccan Arabic Offensive Language Dataset

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8th International Conference on Arabic Language Processing

作者： Zarnoufi, Randa Hajhouj, Mohammed Bachri, Walid Jaafar, Hamid Abik, Mounia Mohammed V Univ Rabat Rabat Morocco Hassan II Univ Casablanca Morocco

ISBN: (纸本)9783031804373;9783031804380

Moroccan Arabic (MA) dialect is a low resource language. To perform any NLP task, we have to develop the necessary resources from scratch. This paper introduces our work on MAOffens, the first MA dataset for offensive language detection. The dataset will serve to build predictive models to detect offensive content widely present on social media and hence help ensure online safety. We built the dataset with a mixture of comments in Arabic and Latin scripts to cover offensiveness in both cases. The resulting dataset consists of 23k comments totally balanced. The dataset is open to the public (https://***/datasets/randa/maoffens). We evaluated the annotation and classification power of the dataset through various classifier architectures. Our best performing classifier was based on a MA transformer model.

关键词： Offensive Language Dataset Moroccan Arabic

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