Ahmed Sabbir Arif

Laxmi Pandey, Ahmed Sabbir Arif

Speech sounds of spoken language are obtained by varying configuration of the articulators surrounding the vocal tract. They contain abundant information that can be utilized to better understand the underlying mechanism of human speech production. We propose a novel deep neural network-based learning framework that understands acoustic information in the variable-length sequence of vocal tract shaping during speech production, captured by real-time magnetic resonance imaging (rtMRI), and translate it into text. The proposed framework comprises of spatiotemporal convolutions, a recurrent network, and the connectionist temporal classification loss, trained entirely end-to-end. On the USC-TIMIT corpus, the model achieved a 40.6% PER at sentence-level, much better compared to the existing models. To the best of our knowledge, this is the first study that demonstrates the recognition of entire spoken sentence based on an individual's articulatory motions captured by rtMRI video. We also performed an analysis of variations in the geometry of articulation in each sub-regions of the vocal tract (i.e., pharyngeal, velar and dorsal, hard palate, labial constriction region) with respect to different emotions and genders. Results suggest that each sub-regions distortion is affected by both emotion and gender.

Ahmed Sabbir Arif, Wolfgang Stuerzlinger, Euclides Jose de Mendonca Filho et al.

We present results of two pilot studies that investigated human error behaviours with an error prone in-air gesture recognizer. During the studies, users performed a small set of simple in-air gestures. In the first study, these gestures were abstract. The second study associated concrete tasks with each gesture. Interestingly, the error patterns observed in the two studies were substantially different.

Anna-Maria Gueorguieva, Gulnar Rakhmetulla, Ahmed Sabbir Arif

This paper presents results of a pilot study that explored the potential of Morse code as a method for text entry on mobile devices. In the study, participants without prior experience with Morse code reached 6.7 wpm with a Morse code keyboard in three short sessions. Learning was observed both in terms of text entry speed and accuracy, which suggests that the overall performance of the keyboard is likely to improve with practice.

Xiumin Shang, Ahmed Sabbir Arif, Marcelo Kallmann

In this paper we address feedback strategies for an autonomous virtual trainer. First, a pilot study was conducted to identify and specify feedback strategies for assisting participants in performing a given task. The task involved sorting virtual cubes according to areas of countries displayed on them. Two feedback strategies were specified. The first provides correctness feedback by fully correcting user responses at each stage of the task, and the second provides suggestive feedback by only notifying if and how a response can be corrected. Both strategies were implemented in a virtual training system and empirically evaluated. The correctness feedback strategy was preferred by the participants, was more effective time-wise, and was more effective in improving task performance skills. The overall system was also rated comparable to hypothetically performing the same task with real interactions.

Ahmed Sabbir Arif

Multi-touch input technologies are becoming popular with the increased interest in touchscreen- and touchpad-based devices. A great deal of work has been done on different multi-touch technologies, and researchers and practitioners are frequently coming up with new ones. However, it is almost impossible to compare such technologies due to the absence of multi-touch performance metrics. Designers usually use their own methods to report their techniques' performances. Moreover, multi-touch interaction was never modeled. That makes it impossible for designers to predict the performance of a new technology before developing it, costing them valuable time, effort, and money. This article discusses the necessity of having dedicated performance metrics and prediction model for multi-touch technologies, and ways of approaching that.

Di "Chelsea" Sun, Vaishnavi Melkote, Ahmed Sabbir Arif

As social media are becoming increasingly popular among young children, it is important to explore this population's needs and requirements from these platforms. As a first step to this, we conducted an exploratory design workshop with children aged between ten and eleven years to find out about their social media needs and requirements. Through an analysis of the paper prototypes solicited from the workshop, here we discuss the social media features that are the most desired by this population.

Monwen Shen, Gulnar Rakhmetulla, Ahmed Sabbir Arif

This paper presents results of a study investing effects of grip rings on text entry. Results revealed that grip rings do not affect text entry performance in terms of speed, accuracy, or keystrokes per character. It then reflects on future research directions based on the results and observations from the study. The purpose of this work is to stress the necessity of classifying and evaluating low-cost mobile phone accessories.

Ohoud Alharbi, Ahmed Sabbir Arif

We propose a research to investigate Saudi peoples' perception of humanoid domestic robots and attitude towards the possibility of having one in their house. Through a series of questionnaires, semi-structured interviews, focus groups, and participatory design sessions, this research will explore Saudi peoples' level of acceptance towards domestic robots, the tasks and responsibilities they would feel comfortable assigning to these robots, their preferred appearance of domestic robots, and the cultural stereotypes they feel a domestic robot must mimic.

Sayan Sarcar, Ahmed Sabbir Arif, Ali Mazalek

With the intention of bringing uniformity to Bengali text entry research, here we present a new approach for calculating the most popular English text entry evaluation metrics for Bengali. To demonstrate our approach, we conducted a user study where we evaluated four popular Bengali text entry techniques.