Publications

Abstract

The increased interest in developing next-gen social robots has raised questions about the factors affecting the perception of robot emotions. This study investigates the impact of robot appearances (human-like, mechanical) and face regions (full-face, eye-region) on human perception of robot emotions. A between-subjects user study (N = 305) was conducted where participants were asked to identify the emotions being displayed in videos of robot faces, as well as a human baseline. Our findings reveal three important insights for effective social robot face design in Human-Robot Interaction (HRI): Firstly, robots equipped with a back-projected, fully animated face – regardless of whether they are more human-like or more mechanical-looking – demonstrate a capacity for emotional expression comparable to that of humans. Secondly, the recognition accuracy of emotional expressions in both humans and robots declines when only the eye region is visible. Lastly, within the constraint of only the eye region being visible, robots with more human-like features significantly enhance emotion recognition.

Abstract

Aims and objectives:
Masked priming lexical decision research involving relatively high-proficient Japanese–English bilinguals suggests that past-tense and present-tense morphological connections (e.g., fell-FALL and looked-LOOK) are represented in their L2 (English) lexicons in a way that is similar to how they are represented in L1 (English) lexicons. The goal of the present research was to determine whether the same is true for low-proficient Japanese–English bilinguals.

Methodology:
Seventy-seven low-proficient Japanese–English bilinguals were tested in the masked priming lexical decision task. We manipulated the morphological or orthographic similarity between L2 English prime-target pairs.

Data and analysis:
We analyzed response latencies and error rates using (generalized) linear mixed-effects models.

Findings:
Although participants responded significantly faster to targets preceded by past-tense primes (e.g., fell-FALL and looked-LOOK) when compared to unrelated primes (e.g., slow-FALL and danger-LOOK), those priming effects were the same size as priming effects produced by orthographically similar primes (e.g., fill-FALL and lonely-LOOK), suggesting that the facilitation from past-tense primes is likely orthographic in nature. Nevertheless, the low-proficient bilinguals showed significant L2-L2 repetition priming (e.g., fall-FALL and look-LOOK), suggesting that, for those individuals, L2 (English) words are at least represented at the lexical level.

Originality:
The present study empirically confirmed a prediction, derived from a post hoc exploratory analysis in our previous research, that masked morphological priming effects are no larger than orthographic priming effects in low-proficient bilinguals. This indicates that a certain level of functional proficiency is required to observe morphological priming effects for Japanese–English bilinguals.

Implications:
Our results suggest that morphological connections in L2 are not yet established for low-proficient bilinguals, even when L2 words are lexically represented in their mental lexicon.

Abstract

Affective behaviors enable social robots to not only establish better connections with humans but also serve as a tool for the robots to express their internal states. It has been well established that emotions are important to signal understanding in Human-Robot Interaction (HRI). This work aims to harness the power of Large Language Models (LLM) and proposes an approach to control the affective behavior of robots. By interpreting emotion appraisal as an Emotion Recognition in Conversation (ERC) tasks, we used GPT-3.5 to predict the emotion of a robot’s turn in real-time, using the dialogue history of the ongoing conversation. The robot signaled the predicted emotion using facial expressions. The model was evaluated in a within-subjects user study (N = 47) where the model-driven emotion generation was compared against conditions where the robot did not display any emotions and where it displayed incongruent emotions. The participants interacted with the robot by playing a card sorting game that was specifically designed to evoke emotions. The results indicated that the emotions were reliably generated by the LLM and the participants were able to perceive the robot’s emotions. It was found that the robot expressing congruent model-driven facial emotion expressions were perceived to be significantly more human-like, emotionally appropriate, and elicit a more positive impression. Participants also scored significantly better in the card sorting game when the robot displayed congruent facial expressions. From a technical perspective, the study shows that LLMs can be used to control the affective behavior of robots reliably in real-time. Additionally, our results could be used in devising novel human-robot interactions, making robots more effective in roles where emotional interaction is important, such as therapy, companionship, or customer service.

Abstract

The current study explored the role of sentential inference in connecting lexical/grammatical knowledge and overall text comprehension in foreign language learning. Using structural equation modeling (SEM), causal relationships were examined between four latent variables: lexical knowledge, grammatical knowledge, sentential inference, and text comprehension. The study analyzed 281 Chinese university students learning Japanese as a second language and compared two causal models: (1) the partially-mediated model, which suggests that lexical knowledge, grammatical knowledge, and sentential inference concurrently influence text comprehension, and (2) the wholly-mediated model, which posits that both lexical and grammatical knowledge impact sentential inference, which then further affects text comprehension. The SEM comparison analysis supported the wholly-mediated model, showing sequential causal relationships from lexical knowledge to sentential inference and then to text comprehension, without significant contribution from grammatical knowledge. The results indicate that sentential inference serves as a crucial bridge between lexical knowledge and text comprehension.

Abstract

This study is the first to report chronometric evidence on Tongan language production. It has been speculated that the mora plays an important role during Tongan phonological encoding. A mora follows the (C)V form, so /a/ and /ka/ (but not /k/) denote a mora in Tongan. Using a picture-word naming paradigm, Tongan native speakers named pictures containing superimposed non-word distractors. This task has been used before in Japanese, Korean, and Vietnamese to investigate the initially selected unit during phonological encoding (IPU). Compared to control distractors, both onset and mora overlapping distractors resulted in faster naming latencies. Several alternative explanations for the pattern of results - proficiency in English, knowledge of Latin script, and downstream effects - are discussed. However, we conclude that Tongan phonological encoding likely natively uses the phoneme, and not the mora, as the IPU..

Abstract

Does the way a word is written influence its spoken production? Previous studies suggest that orthography is involved only when the orthographic representation is highly relevant during speaking (e.g., in reading-aloud tasks). To address this issue, we carried out two experiments using the blocked cyclic picture-naming paradigm. In both experiments, participants were asked to name pictures repeatedly in orthographically homogeneous or heterogeneous blocks. In the naming task, the written form was not shown; however, the radical of the first character overlapped between the four pictures in this block type. A facilitative orthographic effect was found when picture names shared part of their written forms, compared with the heterogeneous condition. This facilitative effect was independent of the position of orthographic overlap (i.e., the left, the lower, or the outer part of the character). These findings strongly suggest that orthography can influence speaking even when it is not highly relevant (i.e., during picture naming) and the orthographic effect is less likely to be attributed to strategic preparation.

Abstract

Bilingual language control (BLC) is a much-debated issue in recent literature. Some models assume BLC is achieved by various types of inhibition of the non-target language, whereas other models do not assume any inhibitory mechanisms. In an event-related potential (ERP) study involving a long-lag morphological priming paradigm, participants were required to name pictures and read aloud words in both their L1 (Dutch) and L2 (English). Switch blocks contained intervening L1 items between L2 primes and targets, whereas non-switch blocks contained only L2 stimuli. In non-switch blocks, target picture names that were morphologically related to the primes were named faster than unrelated control items. In switch blocks, faster response latencies were recorded for morphologically related targets as well, demonstrating the existence of morphological priming in the L2. However, only in non-switch blocks, ERP data showed a reduced N400 trend, possibly suggesting that participants made use of a post-lexical checking mechanism during the switch block.

Abstract

The effect of phonological similarity on L1-L2 cognate translation priming was examined with Japanese-English bilinguals. According to the phonological account, the cognate priming effect for different-script bilinguals consists of additive effects of phonological and conceptual facilitation. If true, then the size of the cognate priming effect would be directly influenced by the phonological similarity of cognate translation equivalents. The present experiment tested and confirmed this prediction: the cognate priming effect was significantly larger for cognate prime-target pairs with high-phonological similarity than pairs with low-phonological similarity. Implications for the nature of lexical processing in same-versus different-script bilinguals are discussed.

Abstract

E-Prime, the software suite by Psychology Software Tools, is used for designing, developing and running custom psychological experiments. Aimed at students and researchers alike, this book provides a much needed, down-to-earth introduction into a wide range of experiments that can be set up using E-Prime. Many tutorials are provided to teach the reader how to develop experiments typical for the broad fields of psychological and cognitive science. Apart from explaining the basic structure of E-Prime and describing how it fits into daily scientific practice, this book also offers an introduction into programming using E-Prime’s own E-Basic language. The authors guide the readers step-by-step through the software, from an elementary to an advanced level, enabling them to benefit from the enormous possibilities for experimental design offered by E-Prime.

Abstract

Not unlike the tonal system in Chinese, Japanese habitually attaches pitch accents to the production of words. However, in contrast to Chinese, few homophonic word-pairs are really distinguished by pitch accents (Shibata & Shibata, 1990). This predicts that pitch accent plays a small role in lexical selection for Japanese language comprehension. The present study investigated whether native Japanese speakers necessarily use pitch accent in the processing of accent-contrasted homophonic pairs (e.g., ame [LH] for 'candy' and ame [HI] for 'rain') measuring electroencephalographic (EEG) potentials. Electrophysiological evidence (i.e., N400) was obtained when a word was semantically incorrect for a given context but not for incorrectly accented homophones. This suggests that pitch accent indeed plays a minor role when understanding Japanese. (C) 2013 Elsevier Ltd. All rights reserved.