Publication

International: Journal, Proceedings & Preprint

Prosody, Speech Act, Intent Argument

• Y. Song and W. I. Cho, "Study on the domain adaption of Korean speech act using daily conversation dataset and petition corpus," in Proc. NLP4DH & IWCLUL, Dec. 2023, pp. 229-234. (Oral only)

• W. I. Cho and N. S. Kim, "Text implicates prosodic ambiguity: A corpus for intention identification of the Korean spoken language," ACM TALLIP, vol. 22, no. 1, Nov. 2022.

• W. I. Cho, S. Moon, J. I. Kim, S. M. Kim, and N. S. Kim, "StyleKQC: A style-variant paraphrase corpus for Korean questions and commands," in Proc. LREC, Jun. 2022, pp. 7122-7128. [arXiv] [Github] (Poster, Virtual)

• W. I. Cho, Y. K. Moon*, S. Moon*, S. M. Kim, and N. S. Kim, "Machines getting with the program: Understanding intent arguments of non-canonical directives," in Findings of ACL: EMNLP 2020, Nov. 2020, pp. 329–339. [arXiv] [Github]

• W. I. Cho, J. Cho, W. H. Kang, and N. S. Kim, "Text matters but speech influences: A computational analysis of syntactic ambiguity resolution ," in Proc. CogSci, Jul. 2020, pp. 1953-1959. [arXiv] [Slide] [Github] (Poster, Virtual)

• W. I. Cho, J. I. Kim, Y. K. Moon, and N. S. Kim, "Discourse component to sentence (DC2S): An efficient human-aided construction of paraphrase and sentence similarity dataset," in Proc. LREC, May 2020, pp. 6819-6826. [Github] (Canceled due to COVID-19 outbreak)

• W. I. Cho,  Y. K. Moon, and N. S. Kim, "Discourse component-based argument extraction of Seoul Korean directives," in Proc. JK 27, Oct. 2019. [Abstract] [Slide] [Github] (Poster)

• W. I. Cho*, J. Cho*, J. Kang, and N. S. Kim, "Prosody-semantics interface in Seoul Korean: Corpus for a disambiguation of wh- intervention," in Proc. ICPhS, Aug. 2019, pp. 3902-3906. [Slide] [Github] (Poster)

• W. I. Cho, H. S. Lee, J. W. Yoon, S. M. Kim, and N. S. Kim, "Speech intention understanding in a head-final language: A disambiguation utilizing intonation-dependency," arXiv preprint arXiv:1811.04231, Nov. 2018. [Github]

• W. I. Cho, Y. K. Moon, W. H. Kang, and N. S. Kim, "Extracting arguments from Korean question and command: An annotated corpus for structured paraphrasing," arXiv preprint arXiv:1810.04631, Oct. 2018. [Github]
  
  

Dialogue and Conversational Agents

• W. I. Cho, S. Kim, E. Choi, and Y. Jeong, "Assessing how users display self-disclosure and authenticity in conversation with human-like agents: A case study of Luda Lee," in Findings of ACL: AACL-IJCNLP 2022, Nov. 2022, pp. 145-152. 

• W. I. Cho*, Y. K. Lee*, S. Bae, J. Kim, S. Park, M. Kim, S. Hahn, and N. S. Kim, "When crowd meets persona: Creating a large-scale open-domain persona dialogue corpus," HCOMP WiP, Nov. 2022. (Poster) [Github]

• W. I. Cho, S. Kim, E. Choi, and Y. Jeong, "Evaluating how users game and display conversation with human-like agents," in Proc. CODI, Oct. 2022, pp. 19-27. (oral only)

• Y. K. Lee*, W. I. Cho*, S. Bae, H. Choi, J. S. Park, N. S. Kim, and S. Hahn, "Feels like I’ve known you forever”: Empathy and self-awareness in human open-domain dialogs," in Proc. CogSci, Jul. 2022. (Poster with abstract) [PsyarXiv]
  
  

Computational Linguistics and Figurative Language

• W. I. Cho, E. Chersoni, Y. Hsu, and C. Huang, "Modeling the Influence of verb aspect on the activation of typical event locations with BERT," in Findings of ACL: ACL 2021, Aug. 2021, pp. 2922-2929. [Github]

• W. I. Cho and N. S. Kim, "Pay attention to categories: Syntax-based sentence modeling with metadata projection matrix," in Proc. PACLIC 34, Oct. 2020, pp. 51-60. (Oral, Virtual)

• W. I. Cho, W. H. Kang, and N. S. Kim, "HashCount at SemEval-2018 Task 3: Concatenative featurization of Tweet and hashtags for irony detection," in Proc. SemEval, Jun. 2018, pp. 546-552. [Slide] (Poster)

• W. I. Cho, W. H. Kang, H. S. Lee, and N. S. Kim, "Detecting oxymoron in a single statement," in Proc. O-COCOSDA, Nov. 2017, pp. 48-52. [Slide] (Oral)
  
  

AI for Social Good, Computational Social Science

• W. I. Cho*, E. Cho*, and H. Shin*, "Three disclaimers for safe disclosure: A cardwriter for reporting the use of generative AI in writing process," arXiv preprint arXiv:2404.09041, Apr. 2024.

• W. I. Cho*, E. Cho*, and K. Cho, "PaperCard: Towards explainable machine assistance in academic writing," EAAMO 2023, Oct. 2023. [arXiv] [hal] (Poster, non-archival)

• S. Min, D. Shin, S. J. Rhee, C. H. K. Park, J. H. Yang, Y. Song, M. J. Kim, K. Kim, W. I. Cho, O. C. Kwon, and Y. M. Ahn, "Acoustic analysis of speech for screening for suicide risk: Machine learning classifiers for between-and within-person evaluation of suicidality," Journal of Medical Internet Research, vol. 25, p.e45456, 2023. 

• K. Yang*, W. Jang*, and W. I. Cho*, "APEACH: Attacking pejorative expressions with analysis on crowd-generated hate speech evaluation datasets," in Findings of ACL: EMNLP 2022, Dec. 2022, pp. 7076–7086. [Github] [arXiv] 

• D. Shin*, K. Kim*, S.-B. Lee, C. Lee, Y. S. Bae, W. I. Cho, M. J. Kim, H. K. C. Park, E. K. Chie, N. S. Kim,  and Y. M. Ahn, "Detection of depression and suicide risk based on text from clinical interviews using machine learning: Possibility of a new objective diagnostic marker," Frontiers Psychiatry, vol. 13, 2022. 

• W. I. Cho and Jihyung Moon, "How does the hate speech corpus concern sociolinguistic discussions? A case study on Korean online news comments," in Proc. NLP4DH, ICON Workshop, Dec. 2021, pp. 13-22. (Oral, Virtual)

• W. I. Cho and S. Kim, "Google-trickers, Yaminjeongeum, and Leetspeak: An empirical taxonomy for intentionally noisy user-generated text," in Proc. W-NUT, EMNLP Workshop, Nov. 2021, pp. 56-61. (Oral, Virtual)

• S. Kim, C. Oh, W. I. Cho, D. Shin, B. Suh, and J. Lee, "Trkic G00gle: Why and how users game translation algorithms," PACM HCI, vol. 5, no. CSCW2, Oct. 2021.

• D. Shin, W. I. Cho, C. H. K. Park, S. J. Rhee, M. J. Kim, H. Lee, N. S. Kim, and Y. M. Ahn, "Detection of minor and major depression through voice as a biomarker using machine learning," Journal of Clinical Medicine, vol. 10, no. 14, 3046, 2021.

• W. I. Cho, S. J. Cheon, W. H. Kang, J. W. Kim, and N. S. Kim, "Giving space to your message: Assistive word segmentation for the electronic typing of digital minorities," in Proc. ACM DIS, Jun. 2021, pp. 1739–1747. [arXiv] [Github] [Video] (Non-ference)

• W. I. Cho*, J. W. Kim*, J. Yang, and N. S. Kim, "Towards cross-lingual generalization of translation gender bias," in Proc. ACM FAccT, Mar. 2021, pp. 449-457. (Oral only, Virtual)

• J. Moon*, W. I. Cho*, and J. Lee, "BEEP! Korean corpus of online news comments for toxic speech detection," in Proc. SocialNLP, ACL Workshop, Jul. 2020, pp. 25-31. [arXiv] [Github] (Oral only, Virtual)

• W. I. Cho, J. W. Kim, S. M. Kim, and N. S. Kim, "On measuring gender bias in translation of gender-neutral pronouns," in Proc. GeBNLP, ACL Workshop, Aug. 2019, pp. 173-181. [Slide] [arXiv] [Github] (Oral)
  
  

Works on Korean NLP

• W. I. Cho, S. Moon, and Y. Song, "Revisiting Korean corpus studies through  technological advances" in Proc. PACLIC, Dec. 2023. (Poster)

• S. Moon, W. I. Cho, H. J. Han, N. Okazaki, and N. S. Kim, "OpenKorPOS: Democratizing Korean tokenization with voting-based open corpus annotation," in Proc. LREC, Jun. 2022, pp. 4975-4983. (Poster, Virtual)

• S. Park*, J. Moon*, S. Kim*, W. I. Cho*, J. Han, J. Park, C. Song, J. Kim, Y. Song, T. Oh, J. Lee, J. Oh, S. Lyu, Y. Jeong, I. Lee, S. Seo, D. Lee, H. Kim, M. Lee, S. Jang, S. Do, S. Kim, K. Lim, J. Lee, K. Park, J. Shin, S. Kim, L. Park, A. Oh, J. Ha, and K. Cho, "KLUE: Korean language understanding evaluation," in Proc. NeurIPS, Track on Datasets and Benchmarks, Dec. 2021. [arXiv] (Poster, Virtual)

• W. I. Cho, S. M. Kim, H. Cho, and N. S. Kim, "kosp2e: Korean speech to English translation corpus," in Proc. Interspeech, Aug. 2021, pp. 3705-3709. [arXiv] [Github] (Virtual)

• W. I. Cho, S. Moon, and Y. Song, "Open Korean corpora: A practical report," in Proc. NLP-OSS, EMNLP Workshop, Nov. 2020, pp. 85–93. [arXiv] [Github] (Oral only, Virtual)

• W. I. Cho, S. M. Kim, and N. S. Kim, "Towards an efficient code-mixed grapheme-to-phoneme conversion in an agglutinative language: A case study on to-Korean transliteration," in Proc. W-CALCS, LREC Workshop, May 2020, pp. 65-70. [Github] (Canceled due to COVID-19 outbreak) 

• W. I. Cho, S. M. Kim, and N. S. Kim, "Investigating an effective character-level embedding in Korean sentence classification," in  Proc. PACLIC 33, Sep. 2019,  pp. 10-18. [Slide] [arXiv] [Github] (Oral)
  
  

Speech and Acoustics

• W. I. Cho, J. Kim, and N. S. Kim, "Cross-modal knowledge distillation with dropout-based confidence," in Proc. APSIPA ASC, Nov. 2022, pp. 653-657. (Oral only)

• H. Y. Kim, J. W . Yoon, W. I. Cho, N. S. Kim, "Neurally optimized decoder for low bitrate speech codec," IEEE Signal Processing Letters, Dec. 2021.

• Y. R. Jo, Y. K. Moon, M. Jung, J. Choi, J. Moon, and W. I. Cho, "VUS at IWSLT 2021: A Finetuned Pipeline for Offline Speech Translation," in Proc. IWSLT, Aug. 2021, pp. 120-124. (Virtual) 

• Y. R. Jo*, Y. K. Moon*, W. I. Cho, and G. S. Jo, "Self-attentive VAD: Context-aware detection of voice from noise," in Proc. ICASSP, Jun. 2021, pp. 6808-6812. (Oral only, Virtual)

• J. W. Yoon, H. Lee, H. Y. Kim, W. I. Cho, and N. S. Kim, "TutorNet: Towards flexible knowledge distillation for end-to-end speech recognition," IEEE/ACM TASLP,  vol. 29, pp. 1626-1638, 2021. [arXiv]

• W. I. Cho, D. Kwak, J. W. Yoon, and N. S. Kim, "Speech to text adaptation: Towards an efficient cross-modal distillation," in Proc. Interspeech, Oct. 2020, pp. 896-900.[arXiv] (Oral only, Virtual)

• I. K. Choi, S. H. Bae, S. J. Cheon, W. I. Cho, and N. S. Kim, "Weakly labeled acoustic event detection using local detector and global classifier," in Proc. APSIPA ASC, Dec. 2017, pp. 1735-1738. (Oral) 

• W. H. Kang, W. I. Cho, S. Y. Jang, H. S. Lee, and N. S. Kim, "I-vector extraction using speaker relevancy for short duration speaker recognition," in Proc. ICITCS 2017, Aug. 2017, pp. 79-87. (Oral)