In Japan, handwriting practice is an important part of education and often involves repeatedly writing the same character, which can become monotonous and reduce motivation. We propose a melody-based handwriting system that maps pen strokes to pitches and stops playback when the stroke leaves a predefined spatial gate, providing spatially-contingent auditory feedback that encourages accurate tracing while maintaining engagement. We implemented a browser-native, low-latency prototype that synchronizes visual input and audio in real time. In a controlled experiment comparing continuous feedback, restricted feedback (proposed), and no feedback, the proposed method led to slower, more attentive writing and a higher proportion of strokes within the designated range, indicating improved precision.

Intrinsic motivation is known to improve task performance when individuals make their own choices. However, when multiple tasks are available, people often choose easier ones even when more difficult or troublesome tasks may be more beneficial. This study investigates whether the phrasing of spoken options can influence such decisions in Voice-based interfaces by leveraging the cognitive and articulatory effort required for vocalization. We conducted a controlled experiment with 40 participants, systematically varying the linguistic complexity of Japanese adverbial phrases in a pointing task and comparing Voice-based and Click-based selection. Results indicated a clear tendency in the voice condition to avoid the most complex phrase and revealed a modality-specific positional tendency in which left-positioned options were chosen more often and right-positioned options were avoided. To our knowledge, this is the first empirical study to demonstrate that vocalization cost can systematically bias task selection in Japanese voice interfaces. These findings suggest that carefully designed spoken language can subtly guide task selection, providing implications for fair and effective voice interface design.

In many shopping sites such as Amazon.com it is possible to view and write reviews of items (products and content). Reviews of items including stories, such as novels, movies, and comics, include reviewers' opinions. Often, these reviews also include descriptions of the story. In some cases, these descriptions may spoil later reader's or viewer's enjoyment and excitement. Hereinafter, we call these descriptions spoilers. Spoilers may be related to the position in the story line. In this study we use story documents. Story documents are documents that record all of the details of the given story. Using the story documents, we investigate the location to which the content of the spoilers correspond in the story documents. Based on the result of the investigation, we consider how to detect spoilers in reviewers' comments.

This short paper proposes a method to classify music video clips uploaded to a video sharing service into music mood categories such as 'cheerful,' 'wistful,' and 'aggressive.' The method leverages viewer comments posted to the music video clips for the music mood classification. It extracts specific features from the comments: (1) adjectives in comments, (2) lengthened words in comments, and (3) comments in chorus sections. Our experimental results classifying 695 video clips into six mood categories showed that our method outperformed the baseline in terms of macro and micro averaged F-measures. In addition, our method outperformed the existing approaches that utilize lyrics and audio signals of songs.

This paper proposes a system called "RerankEverything", which enables users to rerank search results in any search service, such as a Web search engine, an e-commerce site, a hotel reservation site, and so on. This system helps users explore diverse search results. In conventional search services, interactions between users and systems are quite limited and complicated. By using RerankEverything, users can interactively explore search results in accordance with their interests by reranking search results from various viewpoints. Experimental results show that our system potentially help users search more proactively. When using our system, users were more likely to click search results that were initially low ranked. Users also browsed through more diverse search results by reranking search results after giving various types of feedback with our system.

In this paper, we propose a method for helping users explore information via Web searches by using a question and answer (Q&A) corpus archived in a community Q&A site. When users do not have clear information needs and have little knowledge about the task domain, it is difficult for them to create queries that adequately reflect their information needs. We focused on terms like "famous temples," "historical townscapes," and "delicious sweets," which we call "adjective facets", and developed a method of extracting these facets from question and answer archives at a community Q&A site. We evaluated the effectiveness of our adjective facets by comparing them with several baselines.

This paper proposes a system called RerankEverything, which enables users to rerank search results in any search service, such as a Web search engine, an e-commerce site, a hotel reservation site and so on. In conventional search services, interactions between users and services are quite limited and complicated. In addition, search functions and interactions to refine search results differ depending on the services. By using RerankEverything, users can interactively explore search results in accordance with their interests by reranking search results from various viewpoints.

We describe a browser for the past web. It can retrieve data from multiple past web resources and features a passive browsing style based on change detection and presentation. The browser shows past pages one by one along a time line. The parts that were changed between consecutive page versions are animated to reflect their deletion or insertion, thereby drawing the user's attention to them. The browser enables automatic skipping of changeless periods and filtered browsing based on user specified query.