The aim of this paper is to investigate the feasibility of an audio-based context recognition
system. Here, context recognition refers to the automatic classification of the context or an …

Automatic speech recognition (ASR) in children is a rapidly evolving field, as children
become more accustomed to interacting with virtual assistants, such as Amazon Echo …

In this paper, we describe a system for the recognition of musical instruments from isolated
notes or drum samples. We first describe a baseline system that uses mel-frequency cepstral …

This paper presents a hybrid framework of feature extraction and hidden Markov modeling
(HMM) for two-dimensional pattern recognition. Importantly, we explore a new discriminative …

This paper considers a learning framework for speech emotion classification using a
discriminant function based on Gaussian mixture models (GMMs). The GMM parameter set …

The paper concerns the development of a system for the recognition of a context or an
environment based on acoustic information only. Our system uses Mel-frequency cepstral …

Self-regulated learning (SRL) significantly impacts the process and outcome of
programming problem-solving. Studies on SRL behavioural patterns of programming …

In this work, an Automatic Speech Recognition (ASR) system of isolated words for Maithili
dialect is presented. Isolated Word Recognition (IWR) systems recognize a spoken word by …

This paper considers a method for speech emotion recognition by a max-margin framework
incorporating a loss function based on a well-known model called theWatson and Tellegen's …

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to
train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is …