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Found 16 papers, 6 papers with code
Would you like to tell me more? Generating a corpus of psychotherapy dialogues
The acquisition of a dialogue corpus is a key step in the process of training a dialogue model.
Unsupervised Melody-to-Lyric Generation
Automatic melody-to-lyric generation is a task in which song lyrics are generated to go with a given melody.
Unsupervised Melody-Guided Lyrics Generation
At inference time, we leverage the crucial alignments between melody and lyrics and compile the given melody into constraints to guide the generation process.
ExPUNations: Augmenting Puns with Keywords and Explanations
The tasks of humor understanding and generation are challenging and subjective even for humans, requiring commonsense and real-world knowledge to master.
Towards Large-Scale Interpretable Knowledge Graph Reasoning for Dialogue Systems
Our proposed method allows a single transformer model to directly walk on a large-scale knowledge graph to generate responses.
Logical Reasoning for Task Oriented Dialogue Systems
We observe that transformer based models such as UnifiedQA-T5 can be fine-tuned to perform logical reasoning (such as numerical and categorical attributes' comparison) over attributes that been seen in training time (e. g., accuracy of 90\%+ for comparison of smaller than $k_{\max}$=5 values over heldout test dataset).
Emotion Carrier Recognition from Personal Narratives
In this work, we propose a novel task for Narrative Understanding: Emotion Carrier Recognition (ECR).
Is this Dialogue Coherent? Learning from Dialogue Acts and Entities
In this work, we investigate the human perception of coherence in open-domain dialogues.
Annotation of Emotion Carriers in Personal Narratives
We are interested in the problem of understanding personal narratives (PN) - spoken or written - recollections of facts, events, and thoughts.
Affective Behaviour Analysis of On-line User Interactions: Are On-line Support Groups more Therapeutic than Twitter?
Possible applications of the method include provision of guidelines that highlight potential implications of using such platforms on users' mental health, and/or support in the analysis of their impact on specific individuals.
Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning
Natural Language Understanding (NLU) models are typically trained in a supervised learning framework.
Modeling user context for valence prediction from narratives
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. early diagnosis of mental diseases, supervision of disease course, etc.).
Towards Coherent and Engaging Spoken Dialog Response Generation Using Automatic Conversation Evaluators
Having explicit feedback on the relevance and interestingness of a system response at each turn can be a useful signal for mitigating such issues and improving system quality by selecting responses from different approaches.
Natural Language Generation at Scale: A Case Study for Open Domain Question Answering
Our experiments show the feasibility of learning statistical NLG models for open-domain QA with larger ontologies.
Coherence Models for Dialogue
Nevertheless, both the original grid and its extensions do not model intents, a crucial aspect that has been studied widely in the literature in connection to dialogue structure.
ISO-Standard Domain-Independent Dialogue Act Tagging for Conversational Agents
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 system.
