Galo Castillo-López
Also published as: Galo Castillo-lópez
2025
A Survey of Recent Advances on Turn-taking Modeling in Spoken Dialogue Systems
Galo Castillo-López
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Gael de Chalendar
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Nasredine Semmar
Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology
The rapid growth of dialogue systems adoption to serve humans in daily tasks has increased the realism expected from these systems. One trait of realism is the way speaking agents take their turns. We provide here a review of recent methods on turn-taking modeling and thoroughly describe the corpora used in these studies. We observe that 72% of the reviewed works in this survey do not compare their methods with previous efforts. We argue that one of the challenges in the field is the lack of well-established benchmarks to monitor progress. This work aims to provide the community with a better understanding of the current state of research around turn-taking modeling and future directions to build more realistic spoken conversational agents.
2023
Analyzing Zero-Shot transfer Scenarios across Spanish variants for Hate Speech Detection
Galo Castillo-lópez
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Arij Riabi
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Djamé Seddah
Tenth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2023)
Hate speech detection in online platforms has been widely studied inthe past. Most of these works were conducted in English and afew rich-resource languages. Recent approaches tailored forlow-resource languages have explored the interests of zero-shot cross-lingual transfer learning models in resource-scarce scenarios. However, languages variations between geolects such as AmericanEnglish and British English, Latin-American Spanish, and EuropeanSpanish is still a problem for NLP models that often relies on(latent) lexical information for their classification tasks. Moreimportantly, the cultural aspect, crucial for hate speech detection,is often overlooked. In this work, we present the results of a thorough analysis of hatespeech detection models performance on different variants of Spanish,including a new hate speech toward immigrants Twitter data set we built to cover these variants. Using mBERT and Beto, a monolingual Spanish Bert-based language model, as the basis of our transfer learning architecture, our results indicate that hate speech detection models for a given Spanish variant are affected when different variations of such language are not considered. Hate speech expressions could vary from region to region where the same language is spoken. Our new dataset, models and guidelines are freely available.