Papers with segmentation task
Extraction of the Argument Structure of Tokyo Metropolitan Assembly Minutes: Segmentation of Question-and-Answer Sets (2020.lrec-1)
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Keiichi Takamaru, Yasutomo Kimura, Hideyuki Shibuki, Hokuto Ototake, Yuzu Uchida, Kotaro Sakamoto, Madoka Ishioroshi, Teruko Mitamura, Noriko Kando
| Challenge: | a study analyzed local assembly minutes in Japan using a unified format . local assembly minute data is expensive to analyze because of the different ways they are released to the public. |
| Approach: | They construct a corpus of Japanese local assembly minutes based on local autonomy law . they structured all statements in assembly minutes and extracted question and answer pairs . |
| Outcome: | The results show that the minutes are the primary information for local politics. |
Free as in Free Word Order: An Energy Based Model for Word Segmentation and Morphological Tagging in Sanskrit (D18-1)
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Amrith Krishna, Bishal Santra, Sasi Prasanth Bandaru, Gaurav Sahu, Vishnu Dutt Sharma, Pavankumar Satuluri, Pawan Goyal
| Challenge: | a structured prediction framework is proposed to solve word segmentation and morphological tagging tasks in a free word order language. |
| Approach: | They propose a structured prediction framework that jointly solves word segmentation and morphological tagging tasks in Sanskrit. |
| Outcome: | The proposed model outperforms the state of the art with an F-Score of 96.92 (percentage improvement of 7.06%) while using less than one tenth of the task-specific training data. |
Word Segmentation as Unsupervised Constituency Parsing (2022.acl-long)
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| Challenge: | Existing theories of word identification from continuous inputs are based on statistical cues, such as Bayesian inference and normative statistics. |
| Approach: | They propose a model which allows for a process isomorphic to unsupervised constituency parsing and which can reproduce human behavior in word identification experiments. |
| Outcome: | The proposed model reproduces human behavior in word identification experiments, suggesting it is viable to study word identification and its relation to syntactic processing. |
Assessing the State of the Art in Scene Segmentation (2025.naacl-long)
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| Challenge: | Recent advances in scene segmentation have made it difficult to detect scenes in literary texts. |
| Approach: | They propose to modify existing models to improve detection of scenes in literary texts . they propose to use a training sample generation scheme to alleviate this problem . |
| Outcome: | The proposed model is more robust to different types of texts, while its overall performance is slightly worse than that of BERT-based models. |
A Multimodal Corpus of Expert Gaze and Behavior during Phonetic Segmentation Tasks (L18-1)
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| Challenge: | Phonetic segmentation is the process of splitting speech into distinct phonetic units . methods for automatic segmentation are not always accurate enough . |
| Approach: | They propose to model phonetic segmentation as close as possible to manual segmentation by recording experts performing a segmentation task. |
| Outcome: | This corpus captures human segmentation behavior by recording experts performing a segmentation task. |