Publications associées à Syntactic ambiguity

Interpreting Rhythm as Parsing: Syntactic-Processing Operations Predict the Migration of Visual Flashes as Perceived During Listening to Musical Rhythms

Martin Alois Rohrmeier, Steffen Alexander Herff, Gabriele Cecchetti

Music can be interpreted by attributing syntactic relationships to sequential musical events, and, computationally, such musical interpretation represents an analogous combinatorial task to syntactic processing in language. While this perspective has been ...

Wiley2023

Musical Garden Paths: Evidence for Syntactic Revision Beyond the Linguistic Domain

Martin Alois Rohrmeier, Steffen Alexander Herff, Gabriele Cecchetti

While theoretical and empirical insights suggest that the capacity to represent and process complex syntax is crucial in language as well as other domains, it is still unclear whether specific parsing mechanisms are also shared across domains. Focusing on ...

Wiley2022

Conveying the Perception of Humor Arising from Ambiguous Grammatical Constructs in Human-Chatbot Interaction

Denis Gillet, Juan Carlos Farah, Sandy Ingram, Vandit Sharma

Chatbots have long been advocated for computer-assisted language learning systems to support learners with conversational practice. A particular challenge in such systems is explaining mistakes stemming from ambiguous grammatical constructs. Misplaced modi ...

2021

High gamma response tracks different syntactic structures in homophonous phrases

Silvestro Micera, Fiorenzo Artoni

Syntax is a species-specific component of human language combining a finite set of words in a potentially infinite number of sentences. Since words are by definition expressed by sound, factoring out syntactic information is normally impossible. Here, we c ...

Nature Research2020

Distributionally Robust Mechanism Design

Daniel Kuhn, Cagil Kocyigit, Wolfram Wiesemann

We study a mechanism design problem where an indivisible good is auctioned to multiple bidders, for each of whom it has a private value that is unknown to the seller and the other bidders. The agents perceive the ensemble of all bidder values as a random v ...

2020

Model-based interpretation of floor vibrations for indoor occupant tracking

Ian Smith, Yves Sylvain Gilles Reuland, Slah Drira

Information regarding occupant flows inside buildings is beneficial for applications such as thermal-load control, market research and security enhancement. Existing methodologies for occupant tracking involve data-driven techniques that rely either on rad ...

2019

Pessimistic outcome expectancy does not explain ambiguity aversion in decision-making under uncertainty

Martin Alois Rohrmeier

When faced with a decision, most people like to know the odds and prefer to avoid ambiguity. It has been suggested that this aversion to ambiguity is linked to people's assumption of worst possible outcomes. We used two closely linked behavioural tasks in ...

Nature Research2019

New Approaches to Artistic Synthesis Relying on Visual Perception

Mahmut Sami Arpa

Artists often take advantage of the limitations of the human visual system to create art that provides new experiences for the observers. Similarly, in this thesis, we explore new computational artistic compositions that create new visual experiences by re ...

EPFL2019

Word Sense Consistency in Statistical and Neural Machine Translation

Xiao Pu

Different senses of source words must often be rendered by different words in the target language when performing machine translation (MT). Selecting the correct translation of polysemous words can be done based on the contexts of use. However, state-of-th ...

EPFL2018

Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching

François Fleuret, Anton Ivanov, Stepan Tulyakov

End-to-end deep-learning networks recently demonstrated extremely good performance for stereo matching. However, existing networks are difficult to use for practical applications since (1) they are memory-hungry and unable to process even modest-size image ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018