What Causes the Differences in Communication Styles? A Multicultural Study on Directness and Elaborateness (L18-1)
Copied to clipboard
| Challenge: | Using a multi-cultural approach, we investigated the differences in the communication styles elaborateness and directness of human-computer interaction. |
| Approach: | They propose to design a Spoken Dialogue System which adapts to the user's communication idiosyncrasies and to examine the influence of the user culture and gender on the system's elaborateness and directness. |
| Outcome: | The proposed system could be used to communicate with computers in a human-computer interaction. |
Similar Papers
Comparing Styles across Languages (2023.emnlp-main)
Copied to clipboard
| Challenge: | Communication practices vary across cultures. Inherent differences in how people think and behave influence cultural norms. |
| Approach: | They propose a framework to extract stylistic differences from multilingual language models (LMs) they use a multilingual lexica to consolidate feature importances into comparable lexical categories . |
| Outcome: | The proposed framework generates comprehensive style lexica in any language and consolidates feature importances from LMs into comparable lexical categories. |
Assessing How Users Display Self-Disclosure and Authenticity in Conversation with Human-Like Agents: A Case Study of Luda Lee (2022.findings-aacl)
Copied to clipboard
| Challenge: | Existing studies on how people interact with conversational agents have not investigated the interaction authenticity of human-like agents. |
| Approach: | They construct a taxonomy to discern the users’ self-disclosure in the dialogue and the communication authenticity displayed in the user posting. |
| Outcome: | The proposed taxonomy can be used for future research and industrial development. |
Global Voices, Local Biases: Socio-Cultural Prejudices across Languages (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing studies on human biases are heavily skewed towards Western and European languages . despite growing interest in language models, there are several shortcomings in the literature . |
| Approach: | They scale the Word Embedding Association Test to 24 languages and add culturally relevant information for each language. |
| Outcome: | The proposed language models can reflect and often amplify the effects of bias across linguistic, cultural, and societal borders. |
Towards Style Alignment in Cross-Cultural Translation (2025.acl-long)
Copied to clipboard
| Challenge: | Successful communication relies on the speaker’s intended style aligning with the listener’s interpreted style. |
| Approach: | They propose a method that leverages learned stylistic concepts to encourage LLM translation to appropriately convey cultural communication norms and align style. |
| Outcome: | The proposed method aims to encourage translations to convey cultural communication norms and align style. |
DIRECT: Direct and Indirect Responses in Conversational Text Corpus (2021.findings-emnlp)
Copied to clipboard
| Challenge: | Neural conversation models have been able to generate fluent responses through training on a dialogue corpus, but they lack the ability to reveal the implied intentions of users. |
| Approach: | They propose to train neural conversation models on a dialogue corpus that provides pragmatic paraphrases to advance techniques for natural language understanding in dialogue systems. |
| Outcome: | The proposed corpus provides 71,498 pairs of indirect–direct utterance pairs accompanied by a multi-turn dialogue history extracted from the MultiWoZ dataset. |
It’s What You Say and How You Say It: Investigating the Effect of Linguistic vs. Behavioral Adaptation in Task-Oriented Chatbots (2025.coling-main)
Copied to clipboard
| Challenge: | linguistic adaptation is not known to have a positive impact on dialog success and user perception. |
| Approach: | They evaluate subjective and objective aspects of dialog success and user perceptions through a user study . they also examine linguistic adaptations of dialog agents to determine which aspects influence user perception . |
| Outcome: | The proposed agents can differ in their level of formality and their linguistic style. |
Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Tasks (2023.eacl-main)
Copied to clipboard
| Challenge: | Existing research focuses on task-oriented or open-domain dialogue systems with influence skills. |
| Approach: | They propose to define and introduce a category of social influence dialogue systems that influence users’ cognitive and emotional responses. |
| Outcome: | The proposed system is task-oriented or goal-oriented, but it is not open-domain. |
Do dialogue representations align with perception? An empirical study (2023.eacl-main)
Copied to clipboard
| Challenge: | masked language models produce stronger correlations than auto-regressive models, but humans and models make different response selection mistakes. |
| Approach: | They propose to use spoken conversation as a model to measure human comprehension behaviour. |
| Outcome: | The proposed model outperforms the model which produces the strongest correlation with human responses. |
Challenges and Strategies in Cross-Cultural NLP (2022.acl-long)
Copied to clipboard
Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras, Ilias Chalkidis, Ruixiang Cui, Constanza Fierro, Katerina Margatina, Phillip Rust, Anders Søgaard
| Challenge: | Various efforts have been made to accommodate linguistic diversity and serve speakers of many different languages. |
| Approach: | They propose a framework to examine cultural differences in NLP to better serve users . they argue that cultural knowledge, preferences and values can affect NLP practices . |
| Outcome: | The proposed framework examines how cultural knowledge, preferences and values can affect NLP practices. |
Understanding Cross-Lingual Alignment—A Survey (2024.findings-acl)
Copied to clipboard
| Challenge: | Cross-lingual alignment is the meaningful similarity of representations across languages in multilingual language models. |
| Approach: | They propose a taxonomy of methods to improve cross-lingual alignment . they argue that an effective trade-off between language-neutral and language-specific information is key . |
| Outcome: | The proposed methods can be applied to encoder models and encoder-decoder-only models . they show that language-neutral and language-specific information is key . |