Publications (16)
Is this Dialogue Coherent? Learning from Dialogue Acts and Entities
Alessandra Cervone, Giuseppe Riccardi
In this work, we investigate the human perception of coherence in open-domain dialogues. In particular, we address the problem of annotating and modeling the coherence of next-turn…
Unsupervised Melody-Guided Lyrics Generation
Yufei Tian, Anjali Narayan-Chen, Shereen Oraby +7
Automatic song writing is a topic of significant practical interest. However, its research is largely hindered by the lack of training data due to copyright concerns and challenged…
Emotion Carrier Recognition from Personal Narratives
Aniruddha Tammewar, Alessandra Cervone, Giuseppe Riccardi
Personal Narratives (PN) - recollections of facts, events, and thoughts from one's own experience - are often used in everyday conversations. So far, PNs have mainly been explored…
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
Affective Behaviour Analysis of On-line User Interactions: Are On-line Support Groups more Therapeutic than Twitter?
Giuliano Tortoreto, Evgeny A. Stepanov, Alessandra Cervone +2
The increase in the prevalence of mental health problems has coincided with a growing popularity of health related social networking sites. Regardless of their therapeutic potentia…
Coherence Models for Dialogue
Alessandra Cervone, Evgeny Stepanov, Giuseppe Riccardi
Coherence across multiple turns is a major challenge for state-of-the-art dialogue models. Arguably the most successful approach to automatically learning text coherence is the ent…
Unsupervised Melody-to-Lyric Generation
Yufei Tian, Anjali Narayan-Chen, Shereen Oraby +8
Automatic melody-to-lyric generation is a task in which song lyrics are generated to go with a given melody. It is of significant practical interest and more challenging than uncon…
Logical Reasoning for Task Oriented Dialogue Systems
Sajjad Beygi, Maryam Fazel-Zarandi, Alessandra Cervone +2
In recent years, large pretrained models have been used in dialogue systems to improve successful task completion rates. However, lack of reasoning capabilities of dialogue platfor…
Annotation of Emotion Carriers in Personal Narratives
Aniruddha Tammewar, Alessandra Cervone, Eva-Maria Messner +1
We are interested in the problem of understanding personal narratives (PN) - spoken or written - recollections of facts, events, and thoughts. In PN, emotion carriers are the speec…
ExPUNations: Augmenting Puns with Keywords and Explanations
Jiao Sun, Anjali Narayan-Chen, Shereen Oraby +5
The tasks of humor understanding and generation are challenging and subjective even for humans, requiring commonsense and real-world knowledge to master. Puns, in particular, add t…
Towards Coherent and Engaging Spoken Dialog Response Generation Using Automatic Conversation Evaluators
Sanghyun Yi, Rahul Goel, Chandra Khatri +6
Encoder-decoder based neural architectures serve as the basis of state-of-the-art approaches in end-to-end open domain dialog systems. Since most of such systems are trained with a…
ISO-Standard Domain-Independent Dialogue Act Tagging for Conversational Agents
Stefano Mezza, Alessandra Cervone, Giuliano Tortoreto +2
Dialogue Act (DA) tagging is crucial for spoken language understanding systems, as it provides a general representation of speakers' intents, not bound to a particular dialogue sys…
Towards Large-Scale Interpretable Knowledge Graph Reasoning for Dialogue Systems
Yi-Lin Tuan, Sajjad Beygi, Maryam Fazel-Zarandi +3
Users interacting with voice assistants today need to phrase their requests in a very specific manner to elicit an appropriate response. This limits the user experience, and is par…
Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning
Federico Marinelli, Alessandra Cervone, Giuliano Tortoreto +3
Natural Language Understanding (NLU) models are typically trained in a supervised learning framework. In the case of intent classification, the predicted labels are predefined and…
Natural Language Generation at Scale: A Case Study for Open Domain Question Answering
Alessandra Cervone, Chandra Khatri, Rahul Goel +4
Current approaches to Natural Language Generation (NLG) for dialog mainly focus on domain-specific, task-oriented applications (e.g. restaurant booking) using limited ontologies (u…
Modeling user context for valence prediction from narratives
Aniruddha Tammewar, Alessandra Cervone, Eva-Maria Messner +1
Automated prediction of valence, one key feature of a person's emotional state, from individuals' personal narratives may provide crucial information for mental healthcare (e.g. ea…