Abstract Systems that support expressive, situated natural language interactions are essential for expanding access to complex computing systems, such as robots and databases, to non-experts. Reasoning and learning in such natural language interactions is a[…]
Abstract Social media allows researchers to track societal and cultural changes over time based on language analysis tools. Many of these tools rely on statistical algorithms which need to be tuned to specific types of[…]
Abstract We consider a problem of data collection for semantically rich NLU tasks, where detailed semantics of documents (or utterances) are captured using a complex meaning representation. Previously, data collection for such tasks was either[…]
Abstract While the “deep learning tsunami” continues to define the state of the art in speech and language processing, finite-state transducer grammars developed by linguists and engineers are still widely used in industrial, highly-multilingual settings,[…]
Abstract Adversarial attacks deceive neural network systems by adding carefully crafted perturbations to benign signals. Being almost imperceptible to humans, these attacks pose a severe security threat to the state-of-the-art speech and speaker recognition systems, making[…]
Abstract Since it is increasingly harder to opt out from interacting with AI technology, people demand that AI is capable of maintaining contracts such that it supports agency and oversight of people who are required[…]
Abstract Enormous amounts of ever-changing knowledge are available online in diverse textual styles and diverse formats. Recent advances in deep learning algorithms and large-scale datasets are spurring progress in many Natural Language Processing (NLP) tasks,[…]
