Kuan-Yu (Menphis) Chen
Kuan-Yu (Menphis) Chen Dep. of CSIE National Taiwan University Taiwan [email protected] http://www.iis.sinica.edu.tw/~kychen/ (Last Update: 2015/1/15) RESEARCH INTERESTS & SKILLS Speech Recognition Language Modeling: Topic Modeling (Latent Dirichlet Allocation, Probabilistic Latent Semantic Analysis, Word-based Topic Modeling, and etc.), Relevance-based Language Modeling, Neural Network-based Language Modeling and Representations Decoding and Search Natural Language Processing Information Retrieval: Pseudo-relevance Feedback, Language Modeling, Retrieval Models, Spoken Content Retrieval, Diversification Search, Spelling Check Summarization: Sentence Modeling, Ranking Models, Supervised Learning, Spoken Document Summarization Machine Learning & Pattern Recognition Discriminative Training (Global Conditional Log-linear Models, Minimum Error Rate Training, Minimum Classification Error Training, and etc.), Low-rank Matrix Factorization, Deep Neural Network EDUCATION 2010.9 ~ Present: 2007.9 - 2010.7: 2003.9 -2007.6: Ph.D. Candidate, Natural Language Processing Lab., Department of Computer Science and Information Engineering, National Taiwan University Master, Spoken Language Processing Lab., Department of Computer Science and Information Engineering, National Taiwan Normal University Bachelor, Department of Information and Computer Education, National Taiwan Normal University JOB EXPERIENCES 2009.4 ~ Present: 2014.6 ~ 2014.9: Research Assistant, with advisor Prof. Hsin-Min Wang, Institute of Information Science, Academia Sinica, Taiwan Research Intern, IBM T.J. Watson Research Center, Yorktown Heights, New York, USA RESEARCH EXPERIENCES Speech Recognition System Language Modeling Language modeling has been widely used for information retrieval. However, this approach has 2 major challenges. 1) a query is often a vague expression of an underlying information need, 2) there can be word usage mismatch between a query and a document even they are topically related to each other. To mitigate these problems, we proposed a few relevance-based language models using different objective functions to reformulate the original queries. Pseudo-relevance feedback is by far the most commonly-used paradigm for query reformulation. In general, top-ranked documents obtained from the initial retrieval are used for query modeling (reformulation). However, this approach will not work well when the top-ranked documents contain much redundant or non-relevant information. We proposed to glean useful cues from the top-ranked documents to achieve more accurate query representation. Latent semantic analysis and its extensions (such as PLSA and LDA) have been proved the capacity for IR. However, the number of non-occurring words is usually much larger than the number of occurring words in a document. Treating the occurring and non-occurring words with equal importance can be a disadvantage of LSA because the non-occurring words can dominate the estimation of model parameters. We proposed a weighted matrix factorization framework to modulate the impact from occurring and non-occurring words properly. Document Summarization The well-established topic modeling revolves the discovery of “word-document” co-occurrence dependence. Orthogonal to these models, we proposed a word vicinity model (WVM) to explore the “word-word” co-occurrence relationship between words and the long-span latent topic information for IR and speech recognition. Language model framework is sensitive to training data, and it is vulnerable for cross domain applications. To mitigate this deficiency, we proposed a relevance-based dynamic language model adaptation for IR, summarization, and speech recognition. This approach provides a flexible generative framework to render the lexical and topical relationships between observations and the predictions. The state of art i-vector framework which reduces a series of acoustic feature vectors of a speech utterance to a low-dimensional vector representation has demonstrate great performance improvement on language identification and speaker recognition. We adapted this concept to an i-vector based language modeling for information retrieval. Information Retrieval I developed a speech recognition system (especially for Mandarin initial-final phone set) with tree-copy search, three different acoustic look-ahead methods, and naïve n-best generator by using standard C++ STL. Language modeling has been used for unsupervised summarization. However, how to formulate the sentence models and to estimate their parameters for each document to be summarized remains a big challenge. We proposed a novel recurrent neural network language modeling to render word usage cues and long-span structural information of word co-occurrence relationships within documents. Spelling Check Chinese spelling check is still an open problem today. We expand the widely used n-gram based language model by gleaning extra semantic clues and Web resources to enhance the performance using an unsupervised framework. PUBLICATIONS Journal Articles 1. Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang, Ea-Ee Jan, Wen-Lian Hsu, and Hsin-Hsi Chen, "Extractive Broadcast News Summarization Leveraging Recurrent Neural Network Language Modeling Techniques," submitted to IEEE Transactions on Audio, Speech, and Language Processing. (under revision) Kuan-Yu Chen, Hsin-Min Wang, and Hsin-Hsi Chen, "A Probabilistic Framework with Topic Language Modeling for Chinese Spelling Check," submitted to ACM Transactions on Asian Language Information Processing. (under revision) Shih-Hung Liu, Kuan-Yu Chen, Berlin Chen, Hsin-Min Wang, Hsu-Chun Yen, and Wen-Lian Hsu, "Combining Relevance Language Modeling and Clarity Measure for Extractive Speech Summarization," submitted to IEEE Transactions on Audio, Speech, and Language Processing. (under revision) Berlin Chen, Yi-Wen Chen, Kuan-Yu Chen, Hsin-Min Wang, and Kuen-Tyng Yu, "Enhancing Query Formulation for Spoken Document Retrieval," Special Issue on Emerging Technologies and Applications of Artificial Intelligence, Journal of Information Science and Engineering, Vol. 30, No. 3, pp. 553-569, May, 2014. Hsuan-Sheng Chiu, Kuan-Yu Chen, and Berlin Chen, "Leveraging Topical and Positional Cues for Language Modeling in Speech Recognition," Multimedia Tools and Applications, Vol. 72, No. 2, pp. 1465-1481, September, 2014. Berlin Chen, and Kuan-Yu Chen, "Leveraging Relevance Cues for Language Modeling in Speech Recognition," Information Processing & Management, Vol. 49, No. 4, pp. 807-816, July, 2013. Berlin Chen, Kuan-Yu Chen, Pei-Ning Chen, and Yi-Wen Chen, "Spoken Document Retrieval with Unsupervised Query Modeling Techniques," IEEE Transactions on Audio, Speech, and Language Processing, Vol.20, No.9, pp.2602-2612, November, 2012. Kuan-Yu Chen, Hsin-Min Wang, and Berlin Chen, "Spoken Document Retrieval Leveraging Unsupervised and Supervised Topic Modeling Techniques," Special Section: Recent Advances in Multimedia Signal Processing Techniques and Applications, IEICE Transactions on Information and Systems, Vol. E95-D, No.5, pp. 1195-1205, May, 2012. 2. 3. 4. 5. 6. 7. 8. Conference Papers (International Track) 1. Kuan-Yu Chen, Hsin-Min Wang, Berlin Chen, and Hsin-Hsi Chen, "I-vector Based Language Modeling for Query Representation," the 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), Brisbane, Australia, April 19-24, 2015. Kuan-Yu Chen, Ea-Ee Jan, and Tsuyoshi Ide, "Probabilistic Text Analytics Framework for Information Technology Service Desk Tickets," the IFIP/IEEE International Symposium on Integrated Network Management (IM 2015), Ottawa, Canada, May 11-15, 2015. (Short Paper) Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Ea-Ee Jan, Hsin-Min Wang, Wen-Lian Hsu, and Hsin-Hsi Chen, "Leveraging Effective Query Modeling Techniques for Speech Recognition and Summarization," the Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), pp. 1474-1480, Doha, Qatar, October 25-29, 2014. (Short Paper) Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang, Wen-Lian Hsu and Hsin-Hsi Chen, "A Recurrent Neural Network Language Modeling Framework for Extractive Speech 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. Summarization," IEEE International Conference on Multimedia and Expo (ICME 2014), pp. 569-574, Chengdu, China, July 14-18, 2014. (Full Paper) Ea-Ee Jan, Kuan-Yu Chen, and Tsuyoshi Ide, "A Probabilistic Concept Annotation for IT Service Desk Tickets," the Seventh International Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 2014), pp. 21-23, Shanghai, China, November 7, 2014. Shih-Hung Liu, Kuan-Yu Chen, Berlin Chen, Ea-Ee Jan, Hsin-Min Wang, Hsu-Chun Yen, and Wen-Lian Hsu, "A Margin-Based Discriminative Modeling Approach for Extractive Speech Summarization," the APSIPA Annual Summit and Conference (APSIPA 2014), Angkor Wat, Cambodia, December 9-12, 2014. Shih-Hung Liu, Kuan-Yu Chen, Yu-lun Hsieh, Berlin Chen, Hsin-Min Wang, Hsu-Chun Yen and Wen-Lian Hsu, "Enhanced Language Modeling for Extractive Speech Summarization with Sentence Relatedness Information," the Annual Conference of the International Speech Communication Association (INTERSPEECH 2014), Max Atria, Singapore, Sep 14-18, 2014. Kuan-Yu Chen, Hung-Shin Lee, Hsin-Min Wang, Berlin Chen, and Hsin-Hsi Chen, "I-vector Based Language Modeling for Spoken Document Retrieval," the 39th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May 4-9, 2014. Shih-Hung Liu, Kuan-Yu Chen, Yu-Lun Hsieh, Berlin Chen, Hsin-Min Wang, Hsu-Chun Yen, and Wen-Lian Hsu, "Effective Pseudo-relevance Feedback for Language Modeling in Extractive Speech Summarization," the 39th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), Florence, Italy, May 4-9, 2014. Berlin Chen, Yi-Wen Chen, Kuan-Yu Chen, and Ea-Ee Jan, "Effective Pseudo-Relevance Feedback for Language Modeling in Speech Recognition," IEEE workshop on Automatic Speech Recognition and Understanding (ASRU 2013), pp. 13-18, Olomouc, Czech Republic, December 8-12, 2013. Kuan-Yu Chen, Hung-Shin Lee, Chung-Han Lee, Hsin-Min Wang and Hsin-Hsi Chen, "A Study of Language Modeling for Chinese Spelling Check," the 7th SIGHAN Workshop on Chinese Language Processing (SIGHAN-7), pp. 79-83, Nagoya, Japan, Oct 14, 2013. How Jing, Yu Tsao, Kuan-Yu Chen, and Hsin-Min Wang, "Semantic Naive Bayes Classifier for Document Classification," the 6th International Joint Conference on Natural Language Processing (IJCNLP 2013), pp. 1117-1123, Nagoya, Japan, Oct 14-18, 2013. Kuan-Yu Chen, Hsin-Min Wang, Berlin Chen, and Hsin-Hsi Chen, "Weighted Matrix Factorization for Spoken Document Retrieval," the 38th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), pp. 8530-8534, Vancouver, Canada, May 26-31, 2013. Yi-Wen Chen, Kuan-Yu Chen, Hsin-Min Wang, and Berlin Chen, "Effective Pseudo-Relevance Feedback for Spoken Document Retrieval," the 38th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), pp. 8535-8539, Vancouver, Canada, May 26-31, 2013. Yi-Wen Chen, Bo-Han Hao, Kuan-Yu Chen, and Berlin Chen, "Incorporating Proximity Information for Relevance Language Modeling in Speech Recognition," the 14th Annual Conference of the International Speech Communication Association (Interspeech 2013), pp. 2683-2687, Lyon, France, August 25-29, 2013. Berlin Chen, Hao-Chin Chang, and Kuan-Yu Chen, "Sentence Modeling for Extractive Speech Summarization," IEEE International Conference on Multimedia and Expo (ICME 2013), pp. 1-6, San Jose, California, USA, July 15-19, 2013. Kuan-Yu Chen, Hao-Chin Chang, Berlin Chen, and Hsin-Min Wang, "Word Relevance Modeling for Speech Recognition," the 13th Annual Conference of the International Speech Communication Association (Interspeech 2012), pp. 999-1002, Portland, Oregon, USA, September 9-13, 2012. 18. Berlin Chen, Pei-Ning Chen, and Kuan-Yu Chen, "Query Modeling for Spoken Document Retrieval," IEEE workshop on Automatic Speech Recognition and Understanding (ASRU 2011), pp. 389-394, Hawaii, USA, December 11-15, 2011. 19. Pei-Ning Chen, Kuan-Yu Chen, and Berlin Chen, "Leveraging Relevance Cues for Improved Spoken Document Retrieval," the 12th Annual Conference of the International Speech Communication Association (Interspeech 2011), pp. 929-932, Florence, Italy, August 28-31, 2011. 20. Kuan-Yu Chen, and Berlin Chen, "Relevance Language Modeling for Speech Recognition," the 36th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2011), pp. 5568-5571, Prague, Czech, May 22-27, 2011. 21. Kuan-Yu Chen, and Berlin Chen, "A Study of Topic Modeling Techniques for Spoken Document Retrieval," APSIPA Annual Summit and Conference (APSIPA 2010), pp. 237-242, Biopolis, Singapore, December 14-17, 2010. 22. Kuan-Yu Chen, Hsuan-Sheng Chiu, and Berlin Chen, "Latent Topic Modeling of Word Vicinity Information for Speech Recognition," the 35th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), pp. 5394-5397, Dallas, Texas, USA, March 14-19, 2010. 23. Hsuan-Sheng Chiu, Kuan-Yu Chen, Chun-Jen Lee, and Berlin Chen, "Position Information for Language Modeling in Speech Recognition," the 6th International Symposium on Chinese Spoken Language Processing (ISCSLP 2008), pp. 1-4, Kunming, China, December 16-19, 2008. Conference Papers (Domestic Track) 1. Shih-Hung Liu, Kuan-Yu Chen, Hsin-Min Wang, Wen-Lian Hsu, and Berlin Chen, "Improved Sentence Modeling Techniques for Extractive Speech Summarization," ROCLING XXV: Conference on Computational Linguistics and Speech Processing (ROCLING 2013), 2013. Bo-Han Hao, Yi-Wen Chen, Kuan-Yu Chen, and Berlin Chen, "An Empirical Study of Exploring Proximity Information for Improved Language Modeling," 2013 National Computer Symposium (NCS 2013), 2013. Shih-Hung Liu, Kuan-Yu Chen, Hsin-Min Wang, Wen-Lian Hsu, and Berlin Chen, "An Empirical Study of Extractive Speech Summarization Techniques," 2013 National Computer Symposium (NCS 2013), 2013. Yi-Wen Chen, Jun-Yu Chen, Kuan-Yu Chen, and Berlin Chen, "Empirical Comparisons of Various Pseudo-relevant Document Selection Methods for Improved Spoken Document Retrieval," the 17th Conference on Technologies and Applications of Artificial Intelligence (TAAI 2012), November 16-18, 2012. Bang-Xuan Huang, Hank Hao, Kuan-Yu Chen, and Berlin Chen, "Recurrent Neural Network-based Language Modeling with Relevance Information," ROCLING XXIV: Conference on Computational Linguistics and Speech Processing (ROCLING 2012), 2012. Berlin Chen, Min-Hsuan Lai, Kuan-Yu Chen, and Bang-Xuan Huang, "A Survey on Discriminative Language Modeling for Speech Recognition," ACLCLP Newsletter, Vol. 22, 2011. Min-Hsuan Lai, Bang-Xuan Huang, Kuan-Yu Chen, and Berlin Chen, "Empirical Comparisons of Various Discriminative Language Models for Speech Recognition," ROCLING XXIII: Conference on Computational Linguistics and Speech Processing (ROCLING 2011), 2011. Kuan-Yu Chen, Min-Hsuan Lai, and Berlin Chen, "A Study on Using Word Vicinity Information for Speech Recognition," the 15th Conference on Technologies and Applications of Artificial Intelligence (TAAI 2010), November 18-20, 2010. 2. 3. 4. 5. 6. 7. 8. 9. Feng-Ping Liu, Kuan-Yu Chen, Chia-Wen Liu, Yu-Mei Chang, and Berlin Chen, "On the Use of Discriminative Language Modeling Adaptation for Large Vocabulary Continuous Speech Recognition," the 14th Conference on Technologies and Applications of Artificial Intelligence (TAAI 2009), October 30-31, 2009. 10. Kuan-Yu Chen, and Berlin Chen, "On the Use of Topic Models for Large Vocabulary Continuous Speech Recognition," ROCLING XXI: Conference on Computational Linguistics and Speech Processing (ROCLING 2009), September 1-2, 2009. 11. Ting-Wei Hsu, Kuan-Yu Chen, and Berlin Chen, "An Initial Study on English Continuous Speech Recognition," the 12th Conference on Technologies and Applications of Artificial Intelligence (TAAI 2007), November 16-17, 2007. HONORS AND AWARDS 1. 2. 3. 4. 5. 6. IEEE ICASSP spoken language processing student travel grant, supported by Drs. XD Huang, Alex Acero and Hsiao-Wuen Hon with proceeds from royalties of their book Spoken Language Processing (Prentice Hall, 2001), 2014. Student travel grant, supported by Ministry of Science and Technology, Executive Yuan, Taiwan, 2014. Student travel grant, supported by Ministry of Science and Technology, Executive Yuan, Taiwan, 2013. Best student paper award, "Improved Sentence Modeling Techniques for Extractive Speech Summarization," ROCLING XXV: Conference on Computational Linguistics and Speech Processing, 2013. Best student paper award, "Recurrent Neural Network-based Language Modeling with Relevance Information," ROCLING XXIV: Conference on Computational Linguistics and Speech Processing, 2012. Best student paper award, "Empirical Comparisons of Various Discriminative Language Models for Speech Recognition," ROCLING XXIII: Conference on Computational Linguistics and Speech Processing, 2011. REFERENCES Hsin-Hsi Chen ([email protected]) Professor, Department of Computer Science and Information Engineering, National Taiwan University, Taiwan. Hsin-Min Wang ([email protected]) Research Fellow, Institute of Information Science, Academia Sinica, Taiwan. Berlin Chen ([email protected]) Professor, Department of Computer Science and Information Engineering, National Taiwan Normal University, Taiwan.
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