---
title: "Dialogue Act Recognition in Synchronous and — Tavafi 2013"
description: "The paper asks whether one supervised dialogue act (DA) recognizer can work across very different conversation types."
authors: ["Maryam Tavafi", "Yashar Mehdad", "Shafiq Joty", "Giuseppe Carenini", "Raymond Ng"]
year: 2013
venue: "Proceedings of the SIGDIAL 2013 Conference"
source: "https://aclanthology.org/W13-4017/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/papers/tavafi-2013-dialogue-act-recognition-synchronous-asynchronous/"
---
[Elamur Research](https://md.research.elamur.ai/) · [this page in HTML](https://research.elamur.ai/free/papers/tavafi-2013-dialogue-act-recognition-synchronous-asynchronous/)

[home](https://md.research.elamur.ai/) / [papers](https://md.research.elamur.ai/free/papers/) / [2013](https://md.research.elamur.ai/free/papers/2013/) / Dialogue Act Recognition in Synchronous and Asynchronous Conversations

# Dialogue Act Recognition in Synchronous and Asynchronous Conversations

**Authors:** Maryam Tavafi, [Yashar Mehdad](https://md.research.elamur.ai/free/authors/yashar-mehdad/), [Shafiq Joty](https://md.research.elamur.ai/free/authors/shafiq-joty/), [Giuseppe Carenini](https://md.research.elamur.ai/free/authors/giuseppe-carenini/), [Raymond Ng](https://md.research.elamur.ai/free/authors/raymond-ng/) · **Year:** 2013 · **Venue:** Proceedings of the SIGDIAL 2013 Conference · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/W13-4017/) · [PDF](https://aclanthology.org/W13-4017.pdf) · [OpenAlex](https://openalex.org/W2251584308)

**Citations:** 37 citations (openalex-snapshot · 2026-10-14) · [23](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
The paper asks whether one supervised dialogue act (DA) recognizer can work across very different conversation types. Earlier work usually focused on a single domain. The authors evaluate on four corpora: two asynchronous (email, forum) and two synchronous (meeting, phone). They use a deliberately domain-independent feature set made up of unigram frequencies, utterance length, speaker identity and relative position within a post.

Conversational structure is modeled differently by modality. Spoken data uses plain temporal order. Written threads use reply links or a Fragment Quotation Graph, following Joty et al. (2011).

Three learners are compared with 5-fold cross-validation against a majority-class baseline:
- SVM-multiclass, which ignores sequence
- SVM-hmm, a structured sequence model
- CRF, also a structured sequence model

Both sequence models beat SVM-multiclass everywhere, and SVM-hmm is the strongest on every corpus. Results are better on synchronous conversations, which the authors attribute to their simpler sequential structure, and email proves hardest. The study matters because it gives an early cross-modality benchmark and shows that sequence-aware models are worthwhile regardless of domain.

## Key points
- Corpora used:
  - BC3: 40 W3C email threads, 12 DAs
  - CNET: 320 forum threads and 1332 posts, 11 DAs, labeled per post
  - ICSI-MRDA: 75 meetings, reduced to 11 general tags
  - Switchboard-DAMSL (SWBD): 220 tags, mapped to 16 via Jeong (2009)
- SVM-hmm micro-accuracy compared with the majority baseline:
  - BC3: 77.75 vs. 69.56
  - CNET: 58.7 vs. 36.75
  - MRDA: 80.5 vs. 66.47
  - SWBD: 74.32 vs. 46.44
- CRF consistently placed second, with micro-accuracy of 72.18 (BC3), 40.3 (CNET), 77.8 (MRDA) and 73.04 (SWBD). SVM-multiclass barely improved on the baseline.
- Macro-accuracy remained low overall (SVM-hmm best: 17.1–32.4). Rare classes were mostly misclassified as statements, including polite closings, rhetorical questions, self-talk and signal-non-understanding.
- Tools were SVM-light packages for the two SVM models and Mallet for CRF. Planned future work includes POS/syntactic features, prosodic features and semi-supervised learning.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/shelves/linguistics/)

Topics: [Speech act theory](https://md.research.elamur.ai/free/topics/speech-act-theory/)

## Cited by

Cited by

23 papers of our library cite it (of the 140673 whose bibliographies we read); 6 of them have a page here, 17 not yet.

- [Transfer of Corpus-Specific Dialogue Act Annotation to ISO Standard: Is it worth it?](https://md.research.elamur.ai/free/papers/chowdhury-2016-transfer-corpus-specific-dialogue-act/)
- [Modeling Speech Acts in Asynchronous Conversations: A Neural-CRF Approach](https://md.research.elamur.ai/free/papers/joty-2018-modeling-speech-acts-asynchronous-conversations/)
- [Dialogue Act Sequence Labeling using Hierarchical encoder with CRF](https://md.research.elamur.ai/free/papers/kumar-2017-dialogue-act-sequence-labeling-using/)
- [Modeling Local Contexts for Joint Dialogue Act Recognition and Sentiment Classification with Bi-channel Dynamic Convolutions](https://md.research.elamur.ai/free/papers/li-2020-modeling-local-contexts-joint-dialogue/)
- [Extractive Summarization and Dialogue Act Modeling on Email Threads: An Integrated Probabilistic Approach](https://md.research.elamur.ai/free/papers/oya-2014-extractive-summarization-dialogue-act-modeling/)
- [Speaker-change Aware CRF for Dialogue Act Classification](https://md.research.elamur.ai/free/papers/shang-2020-speaker-change-aware-crf-dialogue/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{tavafi2013dialogue,
  title = {{Dialogue Act Recognition in Synchronous and Asynchronous Conversations}},
  author = {Tavafi, Maryam and Mehdad, Yashar and Joty, Shafiq and Carenini, Giuseppe and Ng, Raymond},
  booktitle = {Proceedings of the SIGDIAL 2013 Conference},
  year = {2013},
  doi = {10.14288/1.0052186},
  url = {https://doi.org/10.14288/1.0052186}
}
```

- [← previous Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules](https://md.research.elamur.ai/free/papers/lee-2013-deterministic-coreference-resolution-based-entity/)
- [next → Disambiguating Explicit Discourse Connectives without Oracles](https://md.research.elamur.ai/free/papers/johannsen-2013-disambiguating-explicit-discourse-connectives-without/)
- [↑ back to papers of 2013](https://md.research.elamur.ai/free/papers/2013/)

## References

20 references, 3 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Congkai Sun and Louise-Philippe Morency. 2012. Dialogue Act Recognition using Reweighted Speaker Adaptation. 13th Annual SIGdial Meeting on Discourse and Dialogue. [find](https://scholar.google.com/scholar?q=Congkai+Sun+and+Louise%2DPhilippe+Morency%2E+2012%2E+Dialogue+Act+Recognition+using+Reweighted+Speaker+Adaptation%2E+13th+Annual+SIGdial+Meeting+on+Discourse+and+Dialogue%2E)
2. Dan Jurafsky, Elizabeth Shriberg, and Debra Biasca. 1997. Switchboard SWBD-DAMSL labeling project coder’s manual, draft 13. Technical report, Univ. of Colorado Institute of Cognitive Science. [find](https://scholar.google.com/scholar?q=Dan+Jurafsky%2C+Elizabeth+Shriberg%2C+and+Debra+Biasca%2E+1997%2E+Switchboard+SWBD%2DDAMSL+labeling+project+coder%E2%80%99s+manual%2C+draft+13%2E+Technical+report%2C+Univ%2E+of+Colorado+Institute+of+Cognitive+Science%2E)
3. Elizabeth Shriberg, Raj Dhillon, Sonali Bhagat, Jeremy Ang, and Hannah Carvey. 2004. The ICSI Meeting Recorder Dialog Act (MRDA) Corpus. HLT-NAACL SIGDIAL Workshop. [↗](https://doi.org/10.21236/ada460980) [our card](https://md.research.elamur.ai/free/papers/shriberg-2004-icsi-meeting-recorder-dialog-act/)
4. Gabriel Murray, Giuseppe Carenini, and Raymond T. Ng. 2010. Generating and validating abstracts of meeting conversations: a user study. INLG’10. [find](https://scholar.google.com/scholar?q=Gabriel+Murray%2C+Giuseppe+Carenini%2C+and+Raymond+T%2E+Ng%2E+2010%2E+Generating+and+validating+abstracts+of+meeting+conversations%3A+a+user+study%2E+INLG%E2%80%9910%2E)
5. Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims, and Yasemin Altun. 2004. Support vector machine learning for interdependent and structured output spaces. Proceedings of the 21st International Conference on Machine Learning (ICML). [find](https://scholar.google.com/scholar?q=Ioannis+Tsochantaridis%2C+Thomas+Hofmann%2C+Thorsten+Joachims%2C+and+Yasemin+Altun%2E+2004%2E+Support+vector+machine+learning+for+interdependent+and+structured+output+spaces%2E+Proceedings+of+the+21st+Internation)
6. Jan Ulrich, Gabriel Murray, and Giuseppe Carenini. 2008. A publicly available annotated corpus for supervised email summarization. EMAIL’08 Workshop. AAAI. [find](https://scholar.google.com/scholar?q=Jan+Ulrich%2C+Gabriel+Murray%2C+and+Giuseppe+Carenini%2E+2008%2E+A+publicly+available+annotated+corpus+for+supervised+email+summarization%2E+EMAIL%E2%80%9908+Workshop%2E+AAAI%2E)
7. John Lafferty, Andrew McCallum, and Fernando Pereira. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. Intl. Conf. on Machine Learning. [find](https://scholar.google.com/scholar?q=John+Lafferty%2C+Andrew+McCallum%2C+and+Fernando+Pereira%2E+2001%2E+Conditional+random+fields%3A+Probabilistic+models+for+segmenting+and+labeling+sequence+data%2E+Intl%2E+Conf%2E+on+Machine+Learning%2E)
8. Koby Crammer and Yoram Singer. 2001. On the algorithmic implementation of multiclass kernel-based vector machines. Journal of Machine Learning Research. [find](https://scholar.google.com/scholar?q=Koby+Crammer+and+Yoram+Singer%2E+2001%2E+On+the+algorithmic+implementation+of+multiclass+kernel%2Dbased+vector+machines%2E+Journal+of+Machine+Learning+Research%2E)
9. Lari Carlson. 1983. Dialogue Games: An Approach to Discourse Analysis. D. Reidel. [find](https://scholar.google.com/scholar?q=Lari+Carlson%2E+1983%2E+Dialogue+Games%3A+An+Approach+to+Discourse+Analysis%2E+D%2E+Reidel%2E)
10. Lokesh Shrestha and Kathleen McKeown. 2004. Detection of question-answer pairs in email conversations. Proceedings of the 20th Biennial Int. Conf. on Computational Linguistics. [find](https://scholar.google.com/scholar?q=Lokesh+Shrestha+and+Kathleen+McKeown%2E+2004%2E+Detection+of+question%2Danswer+pairs+in+email+conversations%2E+Proceedings+of+the+20th+Biennial+Int%2E+Conf%2E+on+Computational+Linguistics%2E)
11. Minwoo Jeong, Chin-Yew Lin, and Gary G. Lee. 2009. The Semi-supervised speech act recognition in emails and forums. Proceedings of the 2009 Conf. Empirical Methods in Natural Language Processing. [find](https://scholar.google.com/scholar?q=Minwoo+Jeong%2C+Chin%2DYew+Lin%2C+and+Gary+G%2E+Lee%2E+2009%2E+The+Semi%2Dsupervised+speech+act+recognition+in+emails+and+forums%2E+Proceedings+of+the+2009+Conf%2E+Empirical+Methods+in+Natural+Language+Processing%2E)
12. Oliver Ferschke, Iryna Gurevych, and Yevgen Chebotar. 2012. Behind the Article: Recognizing Dialog Acts in Wikipedia Talk Pages. Proceedings of the 13th Conference of the European Chapter of the ACL. [find](https://scholar.google.com/scholar?q=Oliver+Ferschke%2C+Iryna+Gurevych%2C+and+Yevgen+Chebotar%2E+2012%2E+Behind+the+Article%3A+Recognizing+Dialog+Acts+in+Wikipedia+Talk+Pages%2E+Proceedings+of+the+13th+Conference+of+the+European+Chapter+of+the+ACL%2E) [our card](https://md.research.elamur.ai/free/papers/ferschke-2012-behind-article-recognizing-dialog-acts/)
13. Rajesh Ranganath, Dan Jurafsky, and Dan Mcfarland. 2009. Its not you, its me: Detecting flirting and its misperception in speed-dates. EMNLP-09. [find](https://scholar.google.com/scholar?q=Rajesh+Ranganath%2C+Dan+Jurafsky%2C+and+Dan+Mcfarland%2E+2009%2E+Its+not+you%2C+its+me%3A+Detecting+flirting+and+its+misperception+in+speed%2Ddates%2E+EMNLP%2D09%2E)
14. S. S. Keerthi and S. Sundararajan. 2007. CRF versus SVM-Struct for sequence labeling. Technical report, Yahoo Research. [find](https://scholar.google.com/scholar?q=S%2E+S%2E+Keerthi+and+S%2E+Sundararajan%2E+2007%2E+CRF+versus+SVM%2DStruct+for+sequence+labeling%2E+Technical+report%2C+Yahoo+Research%2E)
15. Shafiq R. Joty, Giuseppe Carenini, and Chin-Yew Lin. 2011. Unsupervised modeling of dialog acts in asynchronous conversations. IJCAI. [find](https://scholar.google.com/scholar?q=Shafiq+R%2E+Joty%2C+Giuseppe+Carenini%2C+and+Chin%2DYew+Lin%2E+2011%2E+Unsupervised+modeling+of+dialog+acts+in+asynchronous+conversations%2E+IJCAI%2E)
16. Su N. Kim, Lawrence Cavedon, and Timothy Baldwin. 2010a. Classifying dialogue acts in one-on-one live chats. EMNLP’10. [find](https://scholar.google.com/scholar?q=Su+N%2E+Kim%2C+Lawrence+Cavedon%2C+and+Timothy+Baldwin%2E+2010a%2E+Classifying+dialogue+acts+in+one%2Don%2Done+live+chats%2E+EMNLP%E2%80%9910%2E) [our card](https://md.research.elamur.ai/free/papers/kim-2010-classifying-dialogue-acts-one-one/)
17. Su N. Kim, Li Wang, and Timothy Baldwin. 2010b. Tagging and linking web forum posts. Proceedings of the Fourteenth Conference on Computational Natural Language Learning, CoNLL ’10. [find](https://scholar.google.com/scholar?q=Su+N%2E+Kim%2C+Li+Wang%2C+and+Timothy+Baldwin%2E+2010b%2E+Tagging+and+linking+web+forum+posts%2E+Proceedings+of+the+Fourteenth+Conference+on+Computational+Natural+Language+Learning%2C+CoNLL+%E2%80%9910%2E)
18. Sujith Ravi and Jihie Kim. 2007. Profiling student interactions in threaded discussions with speech act classifiers. AIED’07, LA, USA. [find](https://scholar.google.com/scholar?q=Sujith+Ravi+and+Jihie+Kim%2E+2007%2E+Profiling+student+interactions+in+threaded+discussions+with+speech+act+classifiers%2E+AIED%E2%80%9907%2C+LA%2C+USA%2E)
19. Vitor R. Carvalho and William W. Cohen. 2005. On the collective classification of email "speech acts". Proceedings of the 31st Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval. [find](https://scholar.google.com/scholar?q=Vitor+R%2E+Carvalho+and+William+W%2E+Cohen%2E+2005%2E+On+the+collective+classification+of+email+%22speech+acts%22%2E+Proceedings+of+the+31st+Annual+Int%2E+ACM+SIGIR+Conf%2E+on+Research+and+Development+in+Information+Re)
20. Yasemin Altun and Ioannis Tsochantaridis and Thomas Hofmann. 2003. Hidden Markov Support Vector Machines. Proceedings of the 20th International Conference on Machine Learning. [find](https://scholar.google.com/scholar?q=Yasemin+Altun+and+Ioannis+Tsochantaridis+and+Thomas+Hofmann%2E+2003%2E+Hidden+Markov+Support+Vector+Machines%2E+Proceedings+of+the+20th+International+Conference+on+Machine+Learning%2E)