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Colexifications for Bootstrapping Cross-lingual Datasets: The Case of Phonology, Concreteness, and Affectiveness 自举跨语言数据集的共化:音系、具体和情感的案例
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2023-06-05 DOI: 10.48550/arXiv.2306.02646
Yiyi Chen, Johannes Bjerva
{"title":"Colexifications for Bootstrapping Cross-lingual Datasets: The Case of Phonology, Concreteness, and Affectiveness","authors":"Yiyi Chen, Johannes Bjerva","doi":"10.48550/arXiv.2306.02646","DOIUrl":"https://doi.org/10.48550/arXiv.2306.02646","url":null,"abstract":"Colexification refers to the linguistic phenomenon where a single lexical form is used to convey multiple meanings. By studying cross-lingual colexifications, researchers have gained valuable insights into fields such as psycholinguistics and cognitive sciences (Jack- son et al., 2019; Xu et al., 2020; Karjus et al., 2021; Schapper and Koptjevskaja-Tamm, 2022; François, 2022). While several multilingual colexification datasets exist, there is untapped potential in using this information to bootstrap datasets across such semantic features. In this paper, we aim to demonstrate how colexifications can be leveraged to create such cross-lingual datasets. We showcase curation procedures which result in a dataset covering 142 languages across 21 language families across the world. The dataset includes ratings of concreteness and affectiveness, mapped with phonemes and phonological features. We further analyze the dataset along different dimensions to demonstrate potential of the proposed procedures in facilitating further interdisciplinary research in psychology, cognitive science, and multilingual natural language processing (NLP). Based on initial investigations, we observe that i) colexifications that are closer in concreteness/affectiveness are more likely to colexify ; ii) certain initial/last phonemes are significantly correlated with concreteness/affectiveness intra language families, such as /k/ as the initial phoneme in both Turkic and Tai-Kadai correlated with concreteness, and /p/ in Dravidian and Sino-Tibetan correlated with Valence; iii) the type-to-token ratio (TTR) of phonemes are positively correlated with concreteness across several language families, while the length of phoneme segments are negatively correlated with concreteness; iv) certain phonological features are negatively correlated with concreteness across languages. The dataset is made public online for further research.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123786843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Transliteration for Cross-Lingual Morphological Inflection 跨语言形态变化的音译
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.22
Nikitha Murikinati, Antonios Anastasopoulos, Graham Neubig
{"title":"Transliteration for Cross-Lingual Morphological Inflection","authors":"Nikitha Murikinati, Antonios Anastasopoulos, Graham Neubig","doi":"10.18653/v1/2020.sigmorphon-1.22","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.22","url":null,"abstract":"Cross-lingual transfer between typologically related languages has been proven successful for the task of morphological inflection. However, if the languages do not share the same script, current methods yield more modest improvements. We explore the use of transliteration between related languages, as well as grapheme-to-phoneme conversion, as data preprocessing methods in order to alleviate this issue. We experimented with several diverse language pairs, finding that in most cases transliterating the transfer language data into the target one leads to accuracy improvements, even up to 9 percentage points. Converting both languages into a shared space like the International Phonetic Alphabet or the Latin alphabet is also beneficial, leading to improvements of up to 16 percentage points.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"22 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123728410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
CLUZH at SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion 多语言字素到音素转换的共享任务
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.19
Peter Makarov, S. Clematide
{"title":"CLUZH at SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion","authors":"Peter Makarov, S. Clematide","doi":"10.18653/v1/2020.sigmorphon-1.19","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.19","url":null,"abstract":"This paper describes the submission by the team from the Institute of Computational Linguistics, Zurich University, to the Multilingual Grapheme-to-Phoneme Conversion (G2P) Task of the SIGMORPHON 2020 challenge. The submission adapts our system from the 2018 edition of the SIGMORPHON shared task. Our system is a neural transducer that operates over explicit edit actions and is trained with imitation learning. It is well-suited for morphological string transduction partly because it exploits the fact that the input and output character alphabets overlap. The challenge posed by G2P has been to adapt the model and the training procedure to work with disjoint alphabets. We adapt the model to use substitution edits and train it with a weighted finite-state transducer acting as the expert policy. An ensemble of such models produces competitive results on G2P. Our submission ranks second out of 23 submissions by a total of nine teams.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132530653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Frustratingly Easy Multilingual Grapheme-to-Phoneme Conversion 令人沮丧的简单多语言字母到音素转换
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.13
Nikhil Prabhu, Katharina Kann
{"title":"Frustratingly Easy Multilingual Grapheme-to-Phoneme Conversion","authors":"Nikhil Prabhu, Katharina Kann","doi":"10.18653/v1/2020.sigmorphon-1.13","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.13","url":null,"abstract":"In this paper, we describe two CU-Boulder submissions to the SIGMORPHON 2020 Task 1 on multilingual grapheme-to-phoneme conversion (G2P). Inspired by the high performance of a standard transformer model (Vaswani et al., 2017) on the task, we improve over this approach by adding two modifications: (i) Instead of training exclusively on G2P, we additionally create examples for the opposite direction, phoneme-to-grapheme conversion (P2G). We then perform multi-task training on both tasks. (ii) We produce ensembles of our models via majority voting. Our approaches, though being conceptually simple, result in systems that place 6th and 8th amongst 23 submitted systems, and obtain the best results out of all systems on Lithuanian and Modern Greek, respectively.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115163114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Joint learning of constraint weights and gradient inputs in Gradient Symbolic Computation with constrained optimization 基于约束优化的梯度符号计算中约束权值与梯度输入的联合学习
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.27
Max Nelson
{"title":"Joint learning of constraint weights and gradient inputs in Gradient Symbolic Computation with constrained optimization","authors":"Max Nelson","doi":"10.18653/v1/2020.sigmorphon-1.27","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.27","url":null,"abstract":"This paper proposes a method for the joint optimization of constraint weights and symbol activations within the Gradient Symbolic Computation (GSC) framework. The set of grammars representable in GSC is proven to be a subset of those representable with lexically-scaled faithfulness constraints. This fact is then used to recast the problem of learning constraint weights and symbol activations in GSC as a quadratically-constrained version of learning lexically-scaled faithfulness grammars. This results in an optimization problem that can be solved using Sequential Quadratic Programming.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116975560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
The SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion 多语言字素到音素转换的SIGMORPHON 2020共享任务
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.2
Kyle Gorman, Lucas F. E. Ashby, Aaron Goyzueta, Arya D. McCarthy, Shijie Wu, Daniel You
{"title":"The SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion","authors":"Kyle Gorman, Lucas F. E. Ashby, Aaron Goyzueta, Arya D. McCarthy, Shijie Wu, Daniel You","doi":"10.18653/v1/2020.sigmorphon-1.2","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.2","url":null,"abstract":"We describe the design and findings of the SIGMORPHON 2020 shared task on multilingual grapheme-to-phoneme conversion. Participants were asked to submit systems which take in a sequence of graphemes in a given language as input, then output a sequence of phonemes representing the pronunciation of that grapheme sequence. Nine teams submitted a total of 23 systems, at best achieving a 18% relative reduction in word error rate (macro-averaged over languages), versus strong neural sequence-to-sequence baselines. To facilitate error analysis, we publicly release the complete outputs for all systems—a first for the SIGMORPHON workshop.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129991861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 48
University of Illinois Submission to the SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection 伊利诺伊大学提交给SIGMORPHON 2020共享任务0:类型学上多样的形态变化
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.15
Marc E. Canby, A. Karipbayeva, B. Lunt, Sahand Mozaffari, Charlotte Yoder, J. Hockenmaier
{"title":"University of Illinois Submission to the SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection","authors":"Marc E. Canby, A. Karipbayeva, B. Lunt, Sahand Mozaffari, Charlotte Yoder, J. Hockenmaier","doi":"10.18653/v1/2020.sigmorphon-1.15","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.15","url":null,"abstract":"The objective of this shared task is to produce an inflected form of a word, given its lemma and a set of tags describing the attributes of the desired form. In this paper, we describe a transformer-based model that uses a bidirectional decoder to perform this task, and evaluate its performance on the 90 languages and 18 language families used in this task.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132047188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
The CMU-LTI submission to the SIGMORPHON 2020 Shared Task 0: Language-Specific Cross-Lingual Transfer CMU-LTI提交给SIGMORPHON 2020共享任务0:特定语言的跨语言迁移
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.6
Nikitha Murikinati, Antonios Anastasopoulos
{"title":"The CMU-LTI submission to the SIGMORPHON 2020 Shared Task 0: Language-Specific Cross-Lingual Transfer","authors":"Nikitha Murikinati, Antonios Anastasopoulos","doi":"10.18653/v1/2020.sigmorphon-1.6","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.6","url":null,"abstract":"This paper describes the CMU-LTI submission to the SIGMORPHON 2020 Shared Task 0 on typologically diverse morphological inflection. The (unrestricted) submission uses the cross-lingual approach of our last year’s winning submission (Anastasopoulos and Neubig, 2019), but adapted to use specific transfer languages for each test language. Our system, with fixed non-tuned hyperparameters, achieved a macro-averaged accuracy of 80.65 ranking 20th among 31 systems, but it was still tied for best system in 25 of the 90 total languages.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133856851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Grapheme-to-Phoneme Conversion with a Multilingual Transformer Model 使用多语言转换模型的字素到音素转换
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.7
Omnia S. ElSaadany, Benjamin Suter
{"title":"Grapheme-to-Phoneme Conversion with a Multilingual Transformer Model","authors":"Omnia S. ElSaadany, Benjamin Suter","doi":"10.18653/v1/2020.sigmorphon-1.7","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.7","url":null,"abstract":"In this paper, we describe our three submissions to the SIGMORPHON 2020 shared task 1 on grapheme-to-phoneme conversion for 15 languages. We experimented with a single multilingual transformer model. We observed that the multilingual model achieves results on par with our separately trained monolingual models and is even able to avoid a few of the errors made by the monolingual models.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122341668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Low-Resource G2P and P2G Conversion with Synthetic Training Data 基于综合训练数据的低资源G2P和P2G转换
Special Interest Group on Computational Morphology and Phonology Workshop Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.sigmorphon-1.12
B. Hauer, Amir Ahmad Habibi, Yixing Luan, Arnob Mallik, Grzegorz Kondrak
{"title":"Low-Resource G2P and P2G Conversion with Synthetic Training Data","authors":"B. Hauer, Amir Ahmad Habibi, Yixing Luan, Arnob Mallik, Grzegorz Kondrak","doi":"10.18653/v1/2020.sigmorphon-1.12","DOIUrl":"https://doi.org/10.18653/v1/2020.sigmorphon-1.12","url":null,"abstract":"This paper presents the University of Alberta systems and results in the SIGMORPHON 2020 Task 1: Multilingual Grapheme-to-Phoneme Conversion. Following previous SIGMORPHON shared tasks, we define a low-resource setting with 100 training instances. We experiment with three transduction approaches in both standard and low-resource settings, as well as on the related task of phoneme-to-grapheme conversion. We propose a method for synthesizing training data using a combination of diverse models.","PeriodicalId":186158,"journal":{"name":"Special Interest Group on Computational Morphology and Phonology Workshop","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121174014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
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