Pranjal P Borah | IIT Jodhpur (original) (raw)

Papers by Pranjal P Borah

Behaviour & Information Technology, 2023

In the field of human-computer interaction, deformable user interfaces are gaining more attention... more In the field of human-computer interaction, deformable user interfaces are gaining more attention. Gestures performed by bending the deformable device are commonly investigated in the literature. These bend gestures' inherent tactile and kinaesthetic feedback and their association with spatial directions benefit both blind and low vision (BLV) and sighted users. Bend gestures are naturally associated with two descriptors of bend, which are location and direction. One potential opportunity to extend this gesture space is to investigate additional descriptors of bend gestures without introducing new locations. In this context, size and angle are the two common additional descriptors of bend gestures. In this work, we conducted two (preliminary and main) studies to investigate BLV and sighted users' performance and preference for multiple magnitude levels of size and angle of bend on a smartphone-sized deformable prototype. Finally, we discuss the results and propose user group-specific design recommendations.

Human Behavior and Emerging Technologies

In human-computer interaction research, prototypes allow for communicating design ideas and condu... more In human-computer interaction research, prototypes allow for communicating design ideas and conducting early user studies to understand user experience without developing the actual product. For investigating deformation-based interaction, functional prototyping becomes challenging due to the unavailability of commercial platforms and the marginal availability of flexible electronic components. During functional prototyping, incurred time and cost are essential factors that further depend on the ease of stiffness customization, reproduction, and upgrade. To offer these advantages, this work presents the fabrication workflow of Nāmya, a smartphone-sized flexible prototype that can detect bend gestures and touch-based inputs using off-the-shelf sensors and flexible materials. This do-it-yourself (DIY) approach to fabricating deformable prototypes focuses on addressing the challenges of selecting flexible material, type of sensor, and sensor positions. We also demonstrate that the prop...

Proceedings of the 10th Indian Conference on Human-Computer Interaction

Reading and drawing geometric shapes are challenging tasks for visually impaired and blind users.... more Reading and drawing geometric shapes are challenging tasks for visually impaired and blind users. The development of a human-centered design solution to address these issues and simulate the techniques of tactile drawing requires a detailed understanding of the process. The objective of this study is to understand the method of reading compound shapes and drawing primitive shapes (triangle and rectangle) to help design digital drawing tool. We conducted a direct observational study of tactile reading and drawing tasks along with semi-structured interviews of 10 visually impaired and blind students. We analyzed the data through affinity analysis and identified a set of validation strategies for drawing and shape identification techniques for reading used by the participants for error prevention and recovery. We present the findings in detail and discuss them in this paper. We believe that the findings will help designers, developers, and researchers to design technology-based interventions for non-visual drawing.

Proceedings of the Thirteenth International Conference on Tangible, Embedded, and Embodied Interaction

The landscape orientation of smartphone offers a better aspect ratio and extensive view for watch... more The landscape orientation of smartphone offers a better aspect ratio and extensive view for watching media and photography. However, it presents challenges of occlusion, reachability, and frequent re-gripping in onehanded interactions. To address these issues we took the opportunity of deformation gestures to interact with future flexible smartphones. A preliminary survey was conducted to understand one-handed landscape mode usage patterns. Then, the 1 st study was conducted to identify 3 most preferred one-handed landscape mode grips. In the 2 nd study, we gathered unique userdefined deformation gestures to identify the set of most natural and intuitive gestures corresponding to each grip. We also found 3 gestures that can be performed in more than one grip. Finally, we discuss the influence of the grips on performing gestures.

Symposium on Spatial User Interaction, 2020

In immersive VR environments, object selection is an essential interaction. However, current obje... more In immersive VR environments, object selection is an essential interaction. However, current object selection techniques suffer from issues of hand jitter, accuracy, and fatigue, especially to select nail-size objects. Here, we present locked dwell time-based point and tap, a novel object selection technique designed for nail-size object selection in a dense virtual environment. The objects are within arm’s reach. We also compare locked dwell time-based point and tap with magnetic grasp, pinch and raycasting. 40 participants evaluated the effectiveness and efficiency of these techniques. The results found that locked dwell time-based point and tap took significantly less task completion time and error rate. It was also the most preferred and caused least effort among all the techniques. We also measured easy to use, easy to learn and perceived naturalness of the techniques.

Named Entity Recognition (NER) is crucial when it comes to taking care of information extraction,... more Named Entity Recognition (NER) is crucial when it comes to taking care of information extraction, question-answering, document summarization and machine translation which are undoubtly the important Natural Language Processing (NLP) tasks. This work is a detailed analysis of our previously developed NER system with more emphasis on how individual features will contribute towards the recognition of person, location and organization named entities and how these features in different combinations affect the performance measure of the system. In addition to these, we have also evaluated the behaviour of the features with the increase in training and test corpus. Since this system is based on supervised learning, we need to have a large parts of speech tagged and named entity tagged Training Corpus as well as a parts of speech tagged Test Corpus. The maximum value of performance measure of the overall system is obtained when the training corpus is of size with 5000 words and the amount o...

Bend gesture-based input on a flexible device requires a distinct indication of gesture completio... more Bend gesture-based input on a flexible device requires a distinct indication of gesture completion. Existing research commonly used threshold-based strategies for discrete input, whereas releasing the bend is used to confirm continuous input. However, the simplest form of these strategies does not allow the rejection of unwanted or unintended input and bi-directional manipulation of the output parameter before confirming continuous input. This work aims to identify user-defined gesture completion strategies with the potential to overcome these drawbacks. Ten blind or low vision (BLV) and fifteen sighted students participated in the study. We identified four and three unique strategies for discrete and continuous inputs, respectively. We believe the reported implications and recommendations with potential application scenarios will help researchers and interaction designers take advantage of these strategies.

Advances in Intelligent Systems and Computing

Word sense ambiguity comes about the use of lexemes associated with more than one sense. In this ... more Word sense ambiguity comes about the use of lexemes associated with more than one sense. In this research work, an improvement has been proposed and evaluated for our previously developed Assamese Word-Sense Disambiguation (WSD) system where potential outcomes of using semantic features were evaluated up to a limited extent. As semantic relationship information has a good effect in most of the natural language processing (NLP) tasks, in this work, the system is developed based on supervised learning approach using Naive Bayes classifier with syntactic as well as semantic features. The performance measure of the overall system has been improved up to 91.11% in terms of F1-measure as compared to 86% of the previously developed system by incorporating the Semantically Related Words (SRW) feature in our feature set.

International Journal on Natural Language Computing, 2014

2014 International Conference on Contemporary Computing and Informatics (IC3I), 2014

In each and every natural language nouns play a very important role. A subcategory of noun is pro... more In each and every natural language nouns play a very important role. A subcategory of noun is proper noun. They represent the names of person, location, organization etc. The task of recognizing the proper nouns in a text and categorizing them into some classes such as person, location, organization and other is called Named Entity Recognition. This is a very essential step of many natural language processing applications that makes the process of information extraction easier. Named Entity Recognition (NER) in most of the Indian languages has been performed using rule-based, supervised and unsupervised approaches. In this work our target language is Assamese, the language spoken by most of the people in North-Eastern part of India and particularly in Assam. In Assamese language, Named Entity Recognition has been performed using the rule based and suffix stripping based approaches. Supervised learning technique is more useful and can be easily adapted to new domains compared to rule based approaches. This paper reports the first work in Assamese NER using a machine learning technique. In this paper Assamese Named Entity Recognition is performed using Naïve Bayes classifier. Since feature extraction plays the most important role in getting better performance in any machine learning technique, in this work our aim is to put forward a description of a few important features related to Assamese NER and performance measure of the system using these features.

2014 International Conference on Contemporary Computing and Informatics (IC3I), 2014

Word sense disambiguation (WSD) can be defined as a task that focuses on estimating the right sen... more Word sense disambiguation (WSD) can be defined as a task that focuses on estimating the right sense of a word in its context. It is important as a pre-processing step in information extraction, machine translation, question answering and many other natural language processing tasks. Ambiguity in Word Sense arises when a particular word has more than one possible sense. Finding the correct sense requires thorough knowledge regarding words. This information of words is often derived from the sources such as words appearing in the context of the target word, part of speech information of the words in the neighbour, syntactical relations and local collocations. Our main aim in this paper is to develop an automatic system for WSD in Assamese using a Naive Bayes classifier. This is the first work to the best of our knowledge on developing an automatic WSD system for Assamese language. Assamese, the main language of most of the people in North-Eastern part of India is a morphologically very rich language. In Assamese WSD is a challenging task because a word can behave differently when combined with a suffix or a sequence of suffixes to have an entirely different sense. WSD often makes use of lexical resources such as WordNet, lexicon, annotated or unannotated corpora etc for its process of disambiguation.

Proceedings of the Fourteenth International Conference on Tangible, Embedded, and Embodied Interaction

Companion Publication of the 2021 Conference on Computer Supported Cooperative Work and Social Computing

Citations are nodes in the networks of knowledge we create. Portals to conversations with the pas... more Citations are nodes in the networks of knowledge we create. Portals to conversations with the past and bonding material with the scholarship of the present. Choosing who we cite is a practice signaling who we recognize and respect as a knowledge source. Therefore, we recognize citations as a relational practice. As this relational characteristic of citing is mediated by wealth we distribute across those who we cite, it is imperative to interrogate how just these practices are. We ought to engage with Citational Justice. Building on recent work discussing citational practices within HCI [9], we use the opportunity of this workshop to expand this conversation into deeper reflection on how we cite and the practices and infrastructures surrounding citations. Our goal with this workshop is * All authors contributed in diverse, yet vital ways, rendering author order meaningless. We center the collective representing our ideas before listing individuals in alphabetical order by first name. Section 4 details authors' roles.

Word sense disambiguation is a technique in the field of natural language processing where the ma... more Word sense disambiguation is a technique in the field of natural language processing where the main task is to find the correct sense in which a word occurs in a particular context. It is found to be of vital help to applications such as question answering, machine translation, text summarization, text classification, information retrieval etc. This has resulted in excessive interest in approaches based on machine learning which performs classification of word senses automatically. The main motivation behind word sense disambiguation is to allow the users to make ample use of the available technologies because ambiguities present in any language provide great difficulty in the use of information technology as words in human language that occur in a particular context can be interpreted in more than one way depending on the context. In this paper we put forward a survey of supervised, unsupervised and knowledge based approaches and algorithms available in word sense disambiguation (WSD).

INTERACT, 2021

Bend gesture-based input on a flexible device requires a distinct indication of gesture completio... more Bend gesture-based input on a flexible device requires a distinct indication of gesture completion. Existing research commonly used threshold-based strategies for discrete input, whereas releasing the bend is used to confirm continuous input. However, the simplest form of these strategies does not allow the rejection of unwanted or unintended input and bi-directional manipulation of the output parameter before confirming continuous input. This work aims to identify user-defined gesture completion strategies with the potential to overcome these drawbacks. Ten blind or low vision (BLV) and fifteen sighted students participated in the study. We identified four and three unique strategies for discrete and continuous inputs, respectively. We believe the reported implications and recommendations with potential application scenarios will help researchers and interaction designers take advantage of these strategies.

ACM TEI, 2020

Students with visual impairment and blindness learn 3D shapes using physical models, which pose p... more Students with visual impairment and blindness learn 3D shapes using physical models, which pose portability issues and high associated costs. Although tactile and kinesthetic feedback systems have been proposed for non-visual exploration of 3D virtual objects, such systems tend to suffer from similar shortcomings. In this research, we propose TMOVE, a low-cost handheld tactile feedback actuator to provide tactile, vibrotactile, and combined feedback for the exploration of virtual space. We conducted a preliminary study with 10 blindfolded sighted participants to compare the perceived 3D experience and the effectiveness of using the feedback modalities in the exploration of two coplanar virtual line segments. We found that all the feedback modalities are equally effective in the exploration of virtual space, and multimodal feedback offers an enhanced 3D perception of virtual objects. We believe the findings presented in this paper will be helpful for designers and researchers in developing low-cost tactile feedback systems.

In immersive VR environments, object selection is an essential interaction. However, current obje... more In immersive VR environments, object selection is an essential interaction. However, current object selection techniques suffer from issues of hand jitter, accuracy, and fatigue, especially to select nail-size objects. Here, we present locked dwell time-based point and tap, a novel object selection technique designed for nail-size object selection in a dense virtual environment. The objects are within arm's reach. We also compare locked dwell time-based point and tap with magnetic grasp, pinch and raycasting. 40 participants evaluated the effectiveness and efficiency of these techniques. The results found that locked dwell time-based point and tap took significantly less task completion time and error rate. It was also the most preferred and caused least effort among all the techniques. We also measured easy to use, easy to learn and perceived naturalness of the techniques.

International Journal on Natural Language Computing, 2014

Named Entity Recognition is always important when dealing with major Natural Language Processing ... more Named Entity Recognition is always important when dealing with major Natural Language Processing tasks such as information extraction, question-answering, machine translation, document summarization etc so in this paper we put forward a survey of Named Entities in Indian Languages with particular reference to Assamese. There are various rule-based and machine learning approaches available for Named Entity Recognition. At the very first of the paper we give an idea of the available approaches for Named Entity Recognition and then we discuss about the related research in this field. Assamese like other Indian languages is agglutinative and suffers from lack of appropriate resources as Named Entity Recognition requires large data sets, gazetteer list, dictionary etc and some useful feature like capitalization as found in English cannot be found in Assamese. Apart from this we also describe some of the issues faced in Assamese while doing Named Entity Recognition.

Behaviour & Information Technology, 2023

In the field of human-computer interaction, deformable user interfaces are gaining more attention... more In the field of human-computer interaction, deformable user interfaces are gaining more attention. Gestures performed by bending the deformable device are commonly investigated in the literature. These bend gestures' inherent tactile and kinaesthetic feedback and their association with spatial directions benefit both blind and low vision (BLV) and sighted users. Bend gestures are naturally associated with two descriptors of bend, which are location and direction. One potential opportunity to extend this gesture space is to investigate additional descriptors of bend gestures without introducing new locations. In this context, size and angle are the two common additional descriptors of bend gestures. In this work, we conducted two (preliminary and main) studies to investigate BLV and sighted users' performance and preference for multiple magnitude levels of size and angle of bend on a smartphone-sized deformable prototype. Finally, we discuss the results and propose user group-specific design recommendations.

Human Behavior and Emerging Technologies

In human-computer interaction research, prototypes allow for communicating design ideas and condu... more In human-computer interaction research, prototypes allow for communicating design ideas and conducting early user studies to understand user experience without developing the actual product. For investigating deformation-based interaction, functional prototyping becomes challenging due to the unavailability of commercial platforms and the marginal availability of flexible electronic components. During functional prototyping, incurred time and cost are essential factors that further depend on the ease of stiffness customization, reproduction, and upgrade. To offer these advantages, this work presents the fabrication workflow of Nāmya, a smartphone-sized flexible prototype that can detect bend gestures and touch-based inputs using off-the-shelf sensors and flexible materials. This do-it-yourself (DIY) approach to fabricating deformable prototypes focuses on addressing the challenges of selecting flexible material, type of sensor, and sensor positions. We also demonstrate that the prop...

Proceedings of the 10th Indian Conference on Human-Computer Interaction

Reading and drawing geometric shapes are challenging tasks for visually impaired and blind users.... more Reading and drawing geometric shapes are challenging tasks for visually impaired and blind users. The development of a human-centered design solution to address these issues and simulate the techniques of tactile drawing requires a detailed understanding of the process. The objective of this study is to understand the method of reading compound shapes and drawing primitive shapes (triangle and rectangle) to help design digital drawing tool. We conducted a direct observational study of tactile reading and drawing tasks along with semi-structured interviews of 10 visually impaired and blind students. We analyzed the data through affinity analysis and identified a set of validation strategies for drawing and shape identification techniques for reading used by the participants for error prevention and recovery. We present the findings in detail and discuss them in this paper. We believe that the findings will help designers, developers, and researchers to design technology-based interventions for non-visual drawing.

Proceedings of the Thirteenth International Conference on Tangible, Embedded, and Embodied Interaction

The landscape orientation of smartphone offers a better aspect ratio and extensive view for watch... more The landscape orientation of smartphone offers a better aspect ratio and extensive view for watching media and photography. However, it presents challenges of occlusion, reachability, and frequent re-gripping in onehanded interactions. To address these issues we took the opportunity of deformation gestures to interact with future flexible smartphones. A preliminary survey was conducted to understand one-handed landscape mode usage patterns. Then, the 1 st study was conducted to identify 3 most preferred one-handed landscape mode grips. In the 2 nd study, we gathered unique userdefined deformation gestures to identify the set of most natural and intuitive gestures corresponding to each grip. We also found 3 gestures that can be performed in more than one grip. Finally, we discuss the influence of the grips on performing gestures.

Symposium on Spatial User Interaction, 2020

In immersive VR environments, object selection is an essential interaction. However, current obje... more In immersive VR environments, object selection is an essential interaction. However, current object selection techniques suffer from issues of hand jitter, accuracy, and fatigue, especially to select nail-size objects. Here, we present locked dwell time-based point and tap, a novel object selection technique designed for nail-size object selection in a dense virtual environment. The objects are within arm’s reach. We also compare locked dwell time-based point and tap with magnetic grasp, pinch and raycasting. 40 participants evaluated the effectiveness and efficiency of these techniques. The results found that locked dwell time-based point and tap took significantly less task completion time and error rate. It was also the most preferred and caused least effort among all the techniques. We also measured easy to use, easy to learn and perceived naturalness of the techniques.

Named Entity Recognition (NER) is crucial when it comes to taking care of information extraction,... more Named Entity Recognition (NER) is crucial when it comes to taking care of information extraction, question-answering, document summarization and machine translation which are undoubtly the important Natural Language Processing (NLP) tasks. This work is a detailed analysis of our previously developed NER system with more emphasis on how individual features will contribute towards the recognition of person, location and organization named entities and how these features in different combinations affect the performance measure of the system. In addition to these, we have also evaluated the behaviour of the features with the increase in training and test corpus. Since this system is based on supervised learning, we need to have a large parts of speech tagged and named entity tagged Training Corpus as well as a parts of speech tagged Test Corpus. The maximum value of performance measure of the overall system is obtained when the training corpus is of size with 5000 words and the amount o...

Bend gesture-based input on a flexible device requires a distinct indication of gesture completio... more Bend gesture-based input on a flexible device requires a distinct indication of gesture completion. Existing research commonly used threshold-based strategies for discrete input, whereas releasing the bend is used to confirm continuous input. However, the simplest form of these strategies does not allow the rejection of unwanted or unintended input and bi-directional manipulation of the output parameter before confirming continuous input. This work aims to identify user-defined gesture completion strategies with the potential to overcome these drawbacks. Ten blind or low vision (BLV) and fifteen sighted students participated in the study. We identified four and three unique strategies for discrete and continuous inputs, respectively. We believe the reported implications and recommendations with potential application scenarios will help researchers and interaction designers take advantage of these strategies.

Advances in Intelligent Systems and Computing

Word sense ambiguity comes about the use of lexemes associated with more than one sense. In this ... more Word sense ambiguity comes about the use of lexemes associated with more than one sense. In this research work, an improvement has been proposed and evaluated for our previously developed Assamese Word-Sense Disambiguation (WSD) system where potential outcomes of using semantic features were evaluated up to a limited extent. As semantic relationship information has a good effect in most of the natural language processing (NLP) tasks, in this work, the system is developed based on supervised learning approach using Naive Bayes classifier with syntactic as well as semantic features. The performance measure of the overall system has been improved up to 91.11% in terms of F1-measure as compared to 86% of the previously developed system by incorporating the Semantically Related Words (SRW) feature in our feature set.

International Journal on Natural Language Computing, 2014

2014 International Conference on Contemporary Computing and Informatics (IC3I), 2014

In each and every natural language nouns play a very important role. A subcategory of noun is pro... more In each and every natural language nouns play a very important role. A subcategory of noun is proper noun. They represent the names of person, location, organization etc. The task of recognizing the proper nouns in a text and categorizing them into some classes such as person, location, organization and other is called Named Entity Recognition. This is a very essential step of many natural language processing applications that makes the process of information extraction easier. Named Entity Recognition (NER) in most of the Indian languages has been performed using rule-based, supervised and unsupervised approaches. In this work our target language is Assamese, the language spoken by most of the people in North-Eastern part of India and particularly in Assam. In Assamese language, Named Entity Recognition has been performed using the rule based and suffix stripping based approaches. Supervised learning technique is more useful and can be easily adapted to new domains compared to rule based approaches. This paper reports the first work in Assamese NER using a machine learning technique. In this paper Assamese Named Entity Recognition is performed using Naïve Bayes classifier. Since feature extraction plays the most important role in getting better performance in any machine learning technique, in this work our aim is to put forward a description of a few important features related to Assamese NER and performance measure of the system using these features.

2014 International Conference on Contemporary Computing and Informatics (IC3I), 2014

Word sense disambiguation (WSD) can be defined as a task that focuses on estimating the right sen... more Word sense disambiguation (WSD) can be defined as a task that focuses on estimating the right sense of a word in its context. It is important as a pre-processing step in information extraction, machine translation, question answering and many other natural language processing tasks. Ambiguity in Word Sense arises when a particular word has more than one possible sense. Finding the correct sense requires thorough knowledge regarding words. This information of words is often derived from the sources such as words appearing in the context of the target word, part of speech information of the words in the neighbour, syntactical relations and local collocations. Our main aim in this paper is to develop an automatic system for WSD in Assamese using a Naive Bayes classifier. This is the first work to the best of our knowledge on developing an automatic WSD system for Assamese language. Assamese, the main language of most of the people in North-Eastern part of India is a morphologically very rich language. In Assamese WSD is a challenging task because a word can behave differently when combined with a suffix or a sequence of suffixes to have an entirely different sense. WSD often makes use of lexical resources such as WordNet, lexicon, annotated or unannotated corpora etc for its process of disambiguation.

Proceedings of the Fourteenth International Conference on Tangible, Embedded, and Embodied Interaction

Companion Publication of the 2021 Conference on Computer Supported Cooperative Work and Social Computing

Citations are nodes in the networks of knowledge we create. Portals to conversations with the pas... more Citations are nodes in the networks of knowledge we create. Portals to conversations with the past and bonding material with the scholarship of the present. Choosing who we cite is a practice signaling who we recognize and respect as a knowledge source. Therefore, we recognize citations as a relational practice. As this relational characteristic of citing is mediated by wealth we distribute across those who we cite, it is imperative to interrogate how just these practices are. We ought to engage with Citational Justice. Building on recent work discussing citational practices within HCI [9], we use the opportunity of this workshop to expand this conversation into deeper reflection on how we cite and the practices and infrastructures surrounding citations. Our goal with this workshop is * All authors contributed in diverse, yet vital ways, rendering author order meaningless. We center the collective representing our ideas before listing individuals in alphabetical order by first name. Section 4 details authors' roles.

Word sense disambiguation is a technique in the field of natural language processing where the ma... more Word sense disambiguation is a technique in the field of natural language processing where the main task is to find the correct sense in which a word occurs in a particular context. It is found to be of vital help to applications such as question answering, machine translation, text summarization, text classification, information retrieval etc. This has resulted in excessive interest in approaches based on machine learning which performs classification of word senses automatically. The main motivation behind word sense disambiguation is to allow the users to make ample use of the available technologies because ambiguities present in any language provide great difficulty in the use of information technology as words in human language that occur in a particular context can be interpreted in more than one way depending on the context. In this paper we put forward a survey of supervised, unsupervised and knowledge based approaches and algorithms available in word sense disambiguation (WSD).

INTERACT, 2021

Bend gesture-based input on a flexible device requires a distinct indication of gesture completio... more Bend gesture-based input on a flexible device requires a distinct indication of gesture completion. Existing research commonly used threshold-based strategies for discrete input, whereas releasing the bend is used to confirm continuous input. However, the simplest form of these strategies does not allow the rejection of unwanted or unintended input and bi-directional manipulation of the output parameter before confirming continuous input. This work aims to identify user-defined gesture completion strategies with the potential to overcome these drawbacks. Ten blind or low vision (BLV) and fifteen sighted students participated in the study. We identified four and three unique strategies for discrete and continuous inputs, respectively. We believe the reported implications and recommendations with potential application scenarios will help researchers and interaction designers take advantage of these strategies.

ACM TEI, 2020

Students with visual impairment and blindness learn 3D shapes using physical models, which pose p... more Students with visual impairment and blindness learn 3D shapes using physical models, which pose portability issues and high associated costs. Although tactile and kinesthetic feedback systems have been proposed for non-visual exploration of 3D virtual objects, such systems tend to suffer from similar shortcomings. In this research, we propose TMOVE, a low-cost handheld tactile feedback actuator to provide tactile, vibrotactile, and combined feedback for the exploration of virtual space. We conducted a preliminary study with 10 blindfolded sighted participants to compare the perceived 3D experience and the effectiveness of using the feedback modalities in the exploration of two coplanar virtual line segments. We found that all the feedback modalities are equally effective in the exploration of virtual space, and multimodal feedback offers an enhanced 3D perception of virtual objects. We believe the findings presented in this paper will be helpful for designers and researchers in developing low-cost tactile feedback systems.

In immersive VR environments, object selection is an essential interaction. However, current obje... more In immersive VR environments, object selection is an essential interaction. However, current object selection techniques suffer from issues of hand jitter, accuracy, and fatigue, especially to select nail-size objects. Here, we present locked dwell time-based point and tap, a novel object selection technique designed for nail-size object selection in a dense virtual environment. The objects are within arm's reach. We also compare locked dwell time-based point and tap with magnetic grasp, pinch and raycasting. 40 participants evaluated the effectiveness and efficiency of these techniques. The results found that locked dwell time-based point and tap took significantly less task completion time and error rate. It was also the most preferred and caused least effort among all the techniques. We also measured easy to use, easy to learn and perceived naturalness of the techniques.

International Journal on Natural Language Computing, 2014

Named Entity Recognition is always important when dealing with major Natural Language Processing ... more Named Entity Recognition is always important when dealing with major Natural Language Processing tasks such as information extraction, question-answering, machine translation, document summarization etc so in this paper we put forward a survey of Named Entities in Indian Languages with particular reference to Assamese. There are various rule-based and machine learning approaches available for Named Entity Recognition. At the very first of the paper we give an idea of the available approaches for Named Entity Recognition and then we discuss about the related research in this field. Assamese like other Indian languages is agglutinative and suffers from lack of appropriate resources as Named Entity Recognition requires large data sets, gazetteer list, dictionary etc and some useful feature like capitalization as found in English cannot be found in Assamese. Apart from this we also describe some of the issues faced in Assamese while doing Named Entity Recognition.