Entity Recognition at First Sight: Improving NER with Eye Movement Information

Previous research shows that eye-tracking data contains information about the lexical and syntactic properties of text, which can be used to improve natural language processing models. In this work, we leverage eye movement features from three corpora with recorded gaze information to augment a state-of-the-art neural model for named entity recognition (NER) with gaze embeddings. These corpora were manually annotated with named entity labels. Moreover, we show how gaze features, generalized on word type level, eliminate the need for recorded eye-tracking data at test time. The gaze-augmented models for NER using token-level and type-level features outperform the baselines. We present the benefits of eye-tracking features by evaluating the NER models on both individual datasets as well as in cross-domain settings.Comment: Accepted at NAACL-HLT 201

Virtual Meeting Rooms: From Observation to Simulation

Much working time is spent in meetings and, as a consequence, meetings have become the subject of multidisciplinary research. Virtual Meeting Rooms (VMRs) are 3D virtual replicas of meeting rooms, where various modalities such as speech, gaze, distance, gestures and facial expressions can be controlled. This allows VMRs to be used to improve remote meeting participation, to visualize multimedia data and as an instrument for research into social interaction in meetings. This paper describes how these three uses can be realized in a VMR. We describe the process from observation through annotation to simulation and a model that describes the relations between the annotated features of verbal and non-verbal conversational behavior.\ud As an example of social perception research in the VMR, we describe an experiment to assess human observers’ accuracy for head orientation

Can you see what i am talking about? Human speech triggers referential expectation in four-month-old infants

Infants’ sensitivity to selectively attend to human speech and to process it in a unique way has been widely reported in the past. However, in order to successfully acquire language, one should also understand that speech is a referential, and that words can stand for other entities in the world. While there has been some evidence showing that young infants can make inferences about the communicative intentions of a speaker, whether they would also appreciate the direct relationship between a specific word and its referent, is still unknown. In the present study we tested four-month-old infants to see whether they would expect to find a referent when they hear human speech. Our results showed that compared to other auditory stimuli or to silence, when infants were listening to speech they were more prepared to find some visual referents of the words, as signalled by their faster orienting towards the visual objects. Hence, our study is the first to report evidence that infants at a very young age already understand the referential relationship between auditory words and physical objects, thus show a precursor in appreciating the symbolic nature of language, even if they do not understand yet the meanings of words

Development of neural responses to hearing their own name in infants at low and high risk for autism spectrum disorder

The own name is a salient stimulus, used by others to initiate social interaction. Typically developing infants orient towards the sound of their own name and exhibit enhanced event-related potentials (ERP) at 5 months. The lack of orientation to the own name is considered to be one of the earliest signs of autism spectrum disorder (ASD). In this study, we investigated ERPs to hearing the own name in infants at high and low risk for ASD, at 10 and 14 months. We hypothesized that low-risk infants would exhibit enhanced frontal ERP responses to their own name compared to an unfamiliar name, while high-risk infants were expected to show attenuation or absence of this difference in their ERP responses. In contrast to expectations, we did not find enhanced ERPs to own name in the low-risk group. However, the high-risk group exhibited attenuated frontal positive-going activity to their own name compared to an unfamiliar name and compared to the low-risk group, at the age of 14 months. These results suggest that infants at high risk for ASD start to process their own name differently shortly after one year of age, a period when frontal brain development is happening at a fast rate

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

Multi-party Interaction in a Virtual Meeting Room

This paper presents an overview of the work carried out at the HMI group of the University of Twente in the domain of multi-party interaction. The process from automatic observations of behavioral aspects through interpretations resulting in recognized behavior is discussed for various modalities and levels. We show how a virtual meeting room can be used for visualization and evaluation of behavioral models as well as a research tool for studying the effect of modified stimuli on the perception of behavior

Speech-Gesture Mapping and Engagement Evaluation in Human Robot Interaction

A robot needs contextual awareness, effective speech production and complementing non-verbal gestures for successful communication in society. In this paper, we present our end-to-end system that tries to enhance the effectiveness of non-verbal gestures. For achieving this, we identified prominently used gestures in performances by TED speakers and mapped them to their corresponding speech context and modulated speech based upon the attention of the listener. The proposed method utilized Convolutional Pose Machine [4] to detect the human gesture. Dominant gestures of TED speakers were used for learning the gesture-to-speech mapping. The speeches by them were used for training the model. We also evaluated the engagement of the robot with people by conducting a social survey. The effectiveness of the performance was monitored by the robot and it self-improvised its speech pattern on the basis of the attention level of the audience, which was calculated using visual feedback from the camera. The effectiveness of interaction as well as the decisions made during improvisation was further evaluated based on the head-pose detection and interaction survey.Comment: 8 pages, 9 figures, Under review in IRC 201

Pointing as an Instrumental Gesture : Gaze Representation Through Indication

The research of the first author was supported by a Fulbright Visiting Scholar Fellowship and developed in 2012 during a period of research visit at the University of Memphis.Peer reviewedPublisher PD

Explorations in engagement for humans and robots

This paper explores the concept of engagement, the process by which individuals in an interaction start, maintain and end their perceived connection to one another. The paper reports on one aspect of engagement among human interactors--the effect of tracking faces during an interaction. It also describes the architecture of a robot that can participate in conversational, collaborative interactions with engagement gestures. Finally, the paper reports on findings of experiments with human participants who interacted with a robot when it either performed or did not perform engagement gestures. Results of the human-robot studies indicate that people become engaged with robots: they direct their attention to the robot more often in interactions where engagement gestures are present, and they find interactions more appropriate when engagement gestures are present than when they are not.Comment: 31 pages, 5 figures, 3 table