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Introduction
Education
June 2016 - June 2020
Publications
Publications (11)
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...
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...
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...
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...
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...
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...
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...
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...
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...
Questions
Questions (2)
Hi everyone,
I am exploring the method and code to construct the Bayesian network for information retrieval using data-driven approach. I do find very old papers where the dataset or code are not available. I am new and exploring this field.
Please, if anyone can provide the code link or suggestion of latest papers that can help to give the implementation view or code for bayesian network construction.
Hi,
I am starting to work in Knowledge graphs and its implementation in Dialogue systems. I cann't find one neither on development of Knowledge graphs nor their implementation in Dialogue system. Most of the paper are describing of knowledge graph embeddings and some deep neural architectures.
Can anyone please recommend some paper to start with , first constructing the knowledge graphs and then its use in dialog systems.
Thanks