Min Li


2022

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MCS: An In-battle Commentary System for MOBA Games
Xiaofeng Qi | Chao Li | Zhongping Liang | Jigang Liu | Cheng Zhang | Yuanxin Wei | Lin Yuan | Guang Yang | Lanxiao Huang | Min Li
Proceedings of the 29th International Conference on Computational Linguistics

This paper introduces a generative system for in-battle real-time commentary in mobile MOBA games. Event commentary is important for battles in MOBA games, which is applicable to a wide range of scenarios like live streaming, e-sports commentary and combat information analysis. The system takes real-time match statistics and events as input, and an effective transform method is designed to convert match statistics and utterances into consistent encoding space. This paper presents the general framework and implementation details of the proposed system, and provides experimental results on large-scale real-world match data.

2018

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DIMSIM: An Accurate Chinese Phonetic Similarity Algorithm Based on Learned High Dimensional Encoding
Min Li | Marina Danilevsky | Sara Noeman | Yunyao Li
Proceedings of the 22nd Conference on Computational Natural Language Learning

Phonetic similarity algorithms identify words and phrases with similar pronunciation which are used in many natural language processing tasks. However, existing approaches are designed mainly for Indo-European languages and fail to capture the unique properties of Chinese pronunciation. In this paper, we propose a high dimensional encoded phonetic similarity algorithm for Chinese, DIMSIM. The encodings are learned from annotated data to separately map initial and final phonemes into n-dimensional coordinates. Pinyin phonetic similarities are then calculated by aggregating the similarities of initial, final and tone. DIMSIM demonstrates a 7.5X improvement on mean reciprocal rank over the state-of-the-art phonetic similarity approaches.

2009

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A Cascade Approach to Extracting Medication Events
Jon Patrick | Min Li
Proceedings of the Australasian Language Technology Association Workshop 2009