Uma Shanker Tiwary

Indian Institute of Information Technology Allahabad | iiita · Information Technology Masters Program

Inter-subject or subject-independent emotion recognition has been a challenging task in affective computing. This work is about an easy-to-implement emotion recognition model that classifies emotions from EEG signals subject independently. It is based on the famous EEGNet architecture, which is used in EEG-related BCIs. We used the Dataset on Emoti...

Generating natural language description for visual content is a technique for describing the content available in the image(s). It requires knowledge of both the domains of computer vision and natural language processing. For this, various models with different approaches are suggested. One of them is encoder-decoder-based description generation. E...

In this paper, we propose a novel method of evaluating text-to-speech systems named “Learning-Based Objective Evaluation” (LBOE), which utilises a set of selected low-level-descriptors (LLD) based features to assess the speech-quality of a TTS model. We have considered Unit selection speech synthesis (USS), Hidden Markov Model speech synthesis (HMM...

Emotion recognition using EEG signals is an emerging area of research due to its broad applicability in Brain-Computer Interfaces. Emotional feelings are hard to stimulate in the lab. Emotions don’t last long, yet they need enough context to be perceived and felt. However, most EEG-related emotion databases either suffer from emotionally irrelevant...

All fruits emit some specific volatile organic compounds (VOCs) during their life cycle. These VOCs have specific characteristics, by using these characteristics fruit ripening stage can be identified without destructing the fruit. In this study, an application-specific electronic nose device was designed for monitoring fruit ripeness. The propose...

We describe the creation of an affective film dataset for researchers interested in studying a spectrum of emotional experiences. We followed a two stage process. In the first stage, two hundred twenty-two video clips with 60-seconds long duration were rated in the lab by 407 participants. Based on the selection criteria, 69 audio-visual clips were...

Emotion recognition using EEG signals is an emerging area of research due to its broad applicability in BCI. Emotional feelings are hard to stimulate in the lab. Emotions do not last long, yet they need enough context to be perceived and felt. However, most EEG-related emotion databases either suffer from emotionally irrelevant details (due to prol...

Availability of naturalistic affective stimuli is needed for creating the affective technological solution as well as making progress in affective science. Although a lot of progress in the collection of affective multimedia stimuli has been made in western countries, the technology and findings based on such monocultural datasets may not be scalab...

Understanding the dynamics of emotional experience is an old problem. However, a clear understanding of the mechanism of emotional experience is still far away. In the presented work, we tried to address this problem using a well-established method called microstate analysis using multichannel electroencephalography (EEG). We recorded the brain act...

This paper presents an improved adversarial network for visual content generation from textual description. Synthesizing high-quality images from the textual description is the most challenging problem in Computer vision. Existing methods first generate the initial image sketch and then refine that to fine-grained details at different portions of t...

While naturalistic stimuli, such as movies, better represent the complexity of the real world and are perhaps crucial to understanding the dynamics of emotion processing, there is limited research on emotions with naturalistic stimuli. There is a need to understand the temporal dynamics of emotion processing and their relationship to different dime...

While naturalistic stimuli like movies better resemble the complexity of the real world and are perhaps crucial to understanding the dynamics of emotion processing, there is limited research on emotions with naturalistic stimuli. There is a need to understand the temporal dynamics of emotion processing and their relationship to different dimensions...

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. Although there is a recent focus on understanding cardiac interoceptive activity and interaction with...

Dialogue policy is a crucial component in task-oriented Spoken Dialogue Systems (SDSs). As a decision function, it takes the current dialogue state as input and generates appropriate system’s response. In this paper, we explore the reinforcement learning approaches to solve this problem in an Indic language scenario. Recently, Deep Reinforcement Le...

Perceptual computing (Per-C) is a branch of CWW (Computing with words) that assist people in making subjective decisions. Their applications take linguistic inputs (i.e., words) from the user and return a linguistic output (i.e., word). The perception of these linguistic inputs suffers from uncertainties, for which IT2FSs (Interval Type-2 Fuzzy Set...

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. While there is a recent focus on understanding cardiac interoceptive activity and interaction with bra...

Hand signs are an effective form of human-to-human communication that has a number of possible applications. Being a natural means of interaction, they are commonly used for communication purposes by speech impaired people worldwide. In fact, about one percent of the Indian population belongs to this category. This is the key reason why it would ha...

Features in a text are hierarchically structured and may not be optimally learned using one-step encoding. Scrutinizing the literature several times facilitates a better understanding of content and helps frame faithful context representations. The proposed model encapsulates the idea of re-examining a piece of text multiple times to grasp the unde...

Various methods in machine learning have noticeable use in generating descriptive text for images and video frames and processing them. This area has attracted the immense interest of researchers in past years. For text generation, various models contain CNN and RNN combined approaches. RNN works well in language modeling; it lacks in maintaining i...

Impreciseness and uncertainty are the fabrics that make life interesting. For decades, human beings have developed strategies to cope with uncertainties and automate them. In personnel selection for the I.T. field, selectors often find it very difficult to select candidates by going through a set of resumes containing similar kinds of skills. Hence...

We describe the creation of an affective film dataset for researchers interested in studying a broad spectrum of emotional experiences. Two hundred twenty-two 60-seconds long video clips were selected based on multimedia content analysis and screened in the lab with 407 participants. The participants' ratings mapped to 31 emotion categories in the...

Analysing expressions on the person's face plays a very vital role in identifying emotions and behavior of a person. Recognizing these expressions automatically results in a crucial component of natural human-machine interfaces. Therefore research in this field has a wide range of applications in bio-metric authentication, surveillance systems , em...

Summaries are expected to relay the most amount of information in the least amount of words. Summary assessment tools such as Rouge, METEOR, and BLEU fail to explain the factual consistency of summaries with source documents and also disregard the synonymy between expressions. Information-coverage is a measure of the amount of important information...

Emotion experiments with naturalistic paradigms are emerging and giving new insights into dynamic brain activity. Context familiarity is considered as an important dimensions of emotion processing by appraisal theorists. However, how the context un/familiarity of the naturalistic stimuli influences the central and autonomic activity is not probed y...

The emotion research with artificial stimuli does not represent the dynamic processing of emotions in real-life situations. The lack of data on emotion with the ecologically valid naturalistic paradigm hinders the knowledge of emotion mechanisms in a real-world interaction. To this aim, we collected the emotional multimedia clips, validated them wi...

Emotion is a constructed phenomenon that emerges from the dynamic interaction of multiple components neurologically, physiologically and behaviorally. Such dynamics can not be captured by static and controlled experiments. Hence, the study of emotion with a naturalistic paradigm is needed. In this dataset, multimedia naturalistic stimuli are used t...

Due to the rapid increase in the development of Task-oriented dialogue systems, the need for labelled dialogue corpus has become inevitable. For the Hindi language, there is no such dialogue corpus yet available. As a first attempt, we release a Hindi Dialogue Restaurant Search (HDRS) corpus and compare various state-of-the-art dialogue state track...

Knowledge sharing platforms like Quora have millions and billions of questions. With such a vast number of questions, there will be a lot of duplicates in it. Duplicate questions in these sites are normal, especially with the increasing number of questions asked. These redundant queries reduce efficiency and create repetitive data on the data serve...

The two-volume set LNCS 12615 + 12616 constitutes the refereed proceedings of the 12th International Conference on Intelligent Human Computer Interaction, IHCI 2020, which took place in Daegu, South Korea, during November 24-26, 2020. The 75 full and 18 short papers included in these proceedings were carefully reviewed and selected from a total of...

The two-volume set LNCS 12615 + 12616 constitutes the refereed proceedings of the 12th International Conference on Intelligent Human Computer Interaction, IHCI 2020, which took place in Daegu, South Korea, during November 24-26, 2020. The 75 full and 18 short papers included in these proceedings were carefully reviewed and selected from a total of...

Repeated reading (RR) helps learners, who have little to no experience with reading fluently to gain confidence, speed and process words automatically. The benefits of repeated readings include helping all learners with fact recall, aiding identification of learners' main ideas and vocabulary, increasing comprehension, leading to faster reading as...

Natural Language Generation (NLG) is a crucial component of a Spoken Dialogue System. Its task is to generate utterances with intended attributes like fluency, variation, readability, scalability and adequacy. As the handcrafted models are rigid and tedious to build, people have proposed many statistical and deep-learning based models to bring abou...

The proposed model unites the robustness of the extractive and abstractive summarization strategies. Three tasks indispensable to automatic summarization, namely, apprehension, extraction, and abstraction, are performed by two specially designed networks, the highlighter RNN and the generator RNN. While the highlighter RNN collectively performs the...

Interval Type-2 fuzzy sets (IT2FSs) are used for modeling uncertainty and imprecision in a better way. In a conversation, the information given by humans are mostly words. IT2FSs can be used to provide a suitable mathematical representation of a word. The IT2FSs can be further processed using Computing with the words (CWW) engine to return the IT2F...

In this work, we perform feature selection on fifty-six prosodic features (such as intensity, formants, pause) extracted from the MIT-interview dataset. These features help in rating the various personality traits (Engaged, Excited, Friendly, Speaking Rate) which in turn help to determine an interviewee performance. First, we have demonstrated how...

This volume constitutes the proceedings of the 11th International Conference on Intelligent Human Computer Interaction, IHCI 2019, held in Allahabad, India, in December 2019. The 25 full papers presented in this volume were carefully reviewed and selected from 73 submissions. The papers are grouped in the following topics: EEG and other biological...

What is an emotion? an old riddle repeatedly being attempted with advance modern tools and understanding of the age. With the new advancement old theories are tested and with correction new is formed. Such is the case with defining emotion broadly shifting from classical definite marker theory to statistically context situated conceptual theory. In...

This book presents select papers from the International Conference on Emerging Trends in Communication, Computing and Electronics (IC3E 2018). Covering the latest theories and methods in three related fields – electronics, communication and computing, it describes cutting-edge methods and applications in the areas of signal and image processing, cy...

This book constitutes the thoroughly refereed proceedings of the 10th International Conference on Intelligent Human Computer Interaction, IHCI 2018, held in Allahabad, India, in December 2018. The 28 regular papers presented were carefully reviewed and selected from 89 submissions. The papers have been organized in the following topical sections: E...

In education, some students lack language comprehension, language production and language acquisition skills. In this paper we extracted several psycholinguistics features broadly grouped into lexical and morphological complexity, syntactic complexity, production units, syntactic pattern density, referential cohesion, connectives, amounts of coordi...

In this paper, an extended combined approach of phrase based statistical machine translation (SMT), example based MT (EBMT) and rule based MT (RBMT) is proposed to develop a novel hybrid data driven MT system capable of outperforming the baseline SMT, EBMT and RBMT systems from which it is derived. In short, the proposed hybrid MT process is guided...

Automatic speech recognition (ASR) and Text to speech (TTS) are two prominent area of research in human computer interaction nowadays. A set of phonetically rich sentences is in a matter of importance in order to develop these two interactive modules of HCI. Essentially, the set of phonetically rich sentences has to cover all possible phone units d...

The algorithm proposed in this paper aims to achieve pose recognition in Indian classical dance domain. Three different dance forms namely Bharatnatyam, Kathak and Odissi, all together with 15 poses have been considered for pose classification problem. An initial database is created consisting of 100 images and split into training and testing datas...

Currently, the research on human affect recognition has shifted from six basic emotions to complex affect recognition in continuous two or three dimensional space due to the following challenges: (i) representing and analyzing large number of emotions in one framework, (ii) representing complex emotions in the framework, and (iii) validating the fr...

In this paper an approach of Semantic Knowledge Extraction (SKE), from a set of research papers, is proposed to develop a system Summarized Research Article Generator (SRAG) which would generate a summarized research article based on the query given by a user. The SRAG stores the semantic knowledge extracted from the query relevant papers in the fo...

EEG based biometric system can be used for authentication, with advantages like confidentiality retention and forgery prevention. Signals which are taken from maximum brain regions show some sort of unique information that can be used for extracting the subject dependent pattern. This paper presents an approach to find the relationships among signa...

Clustering algorithms have been used for systematic retrieval of data by organizing them into several clusters and K-Means is one such algorithm, which partitions data into groups based on distance metric in an unsupervised way. In this paper, we study denoising of images corrupted with variable Gaussian noise spread across the entire images in the...

In this paper we implemented an unobtrusive and non-invasive method to measure pulse rate and heart rate variability. A Ballistocardiography technique has been used which describes ballistic force applied by heart on blood vessels. Ballistocardiography depicts repetitive motion in human body against blood flow because of the ballistic force. In thi...

Successful implementation of type-1 Fuzzy Systems (FS) in diverse application areas have been accomplished till date. Nonetheless type-1 FS are not able to handle significant amount of uncertainties present in dynamic real world applications. An improved performance against these uncertainties is achieved by type-2 FS. In this paper, a type-2 FS is...

The objective of this chapter is twofold. On one hand, it tries to introduce and present various components of Human Computer Interaction (HCI), if HCI is modeled as a process of cognition; on the other hand, it tries to underline those representations and mechanisms which are required to develop a general framework for a collaborative HCI. One mus...

The objective of this paper is two-fold. First, to adapt the earlier cognitive interactive framework for speech retrieval application and second, to enhance the accuracy of continuous speech retrieval system using fuzzy word mesh representing linguistic knowledge of users. The proposed method recognizes the audio query and retrieves the audio file(...

Associationism is one of the dominant theories of learning. It is believed to play an implicit role in formation of inert cognition when provided with proper reinforcements. On the other hand learning by analogy plays an important role in the learning process of humans. Instructors all over the world use analogies to put their point through. We hav...

Automated human quality translation between languages has been an enduring goal in computer science. We have worked on the concept of chunk-based statistical machine translation for the purpose of machine translation between Hindi and English using a probabilistic approach. Translation between Hindi and English is a challenging task as Hindi and En...

In this paper, we present a generic interactive framework based on human cognition, where the system can learn continuously from the Internet and from its interaction with the users. To show the utilization of this framework, Iintelli, an agent based application for multiple text document summarization is developed and compared with the MEAD on the...

In this paper we propose the use of multilevel classification techniques similar to concept of Bayesian belief networks for Combining Words and Pictures (Images) for Museum Information Retrieval. We have designed our own corpus on Allahabad Museum. This approach is static which allows one to compute the rank of documents of relevant words and pictu...

The objective of this chapter is twofold. On one hand, it tries to introduce and present various components of Human Computer Interaction (HCI), if HCI is modeled as a process of cognition; on the other hand, it tries to underline those representations and mechanisms which are required to develop a general framework for a collaborative HCI. One mus...

Spoken dialogue systems are a step forward towards the realization of human-like interaction with computer-based systems. This chapter focuses on issues related to spoken dialog systems. It presents a general architecture for spoken dialogue systems for human-computer interaction, describes its components, and highlights key research challenges in...

Human Computer Interaction is the study of relationships among people and computers. As the digital world is getting multi-modal, the information space is getting more and more complex. In order to navigate this information space and to capture and apply this information to appropriate use, an effective interaction between human and computer is req...

In this paper, we have proposed speech emotion recognition system based on multi-algorithm fusion. Mel Frequency Cepstral Coefficients (MFCC) and Discrete Wavelet Transform (DWT), the two prominent algorithms for speech analysis, have been used to extract emotion information from speech signal. MFCC, a representation of the short-term power spectru...

In this paper, we have investigated the performance of different multi-resolution transforms in the application of emotion recognition from facial images. Multi-resolution analysis of image provides frequency information along with time information in different scale, orientation and locations. The emotion information from facial images was being c...

This paper present an overview of multimodal information fusion strategies such as early, intermediate and late fusion as reported in literature. We also made an experimental evaluation for one of them for multimodal emotion recognition system. Further we propose a fusion scheme based on speech and facial expression for multimodal emotion recogniti...

In this paper, we have proposed a multilevel soft thresholding technique for noise removal in Daubechies complex wavelet transform domain. Two useful properties of Daubechies complex wavelet transform, approximate shift invariance and strong edge representation, have been explored. Most of the uncorrelated noise gets removed by shrinking complex wa...

The purpose of this paper is to evolve a robust text independent speaker identification system based on the wavelet transform, which is able to analyze signal at multiple resolutions. The proposed system identifies speakers by their acoustic characteristics embedded in speech signal of speakers. Features are obtained from approximation and detail c...

Various structural and functional changes associated with ischemic (myocardial infarcted) heart cause amplitude and spectral changes in signals obtained at different leads of ECG. In order to capture these changes, Relative Frequency Band Coefficient (RFBC) features from 12-lead ECG have been proposed and used for automated identification of myocar...