We propose a sparse hidden Markov model (HMM)-based single-channel speech
enhancement method that models the speech and noise gains accurately in non-stationary …

Discovering word-like units without textual transcriptions is an important step in low-resource
speech technology. In this work, we demonstrate a model inspired by statistical machine …

This paper demonstrates three different systems capable of performing the multimodal word
discovery task. A multimodal word discovery system accepts, as input, a database of spoken …

We propose a sparse hidden Markov model (HMM)-based single-channel speech
enhancement method that models the speech and noise gains accurately in both stationary …

Despite the overwhelming use of statistical language models in speech recognition,
machine translation, and several other domains, few high probability guarantees exist on …

In the absence of dictionaries, translators, or grammars, it is still possible to learn some of
the words of a new language by listening to spoken descriptions of images. If several …

Automatic speech recognition has matured into a commercially successful technology,
enabling voice-based interfaces for smartphones, smart TVs, and many other consumer …

Abstract" The main focus of this thesis is to study the stability of fix points for a dynamical
system. In the first part, we consider two dynamical models whose underlying graph can be …

Abstract The design of Speech Recognition system has careful attention in the following
issues: classification of various types of speech classes, speech representation, and feature …

2. T. Taniguchi, MA Johnson, and Y. Ohta,“Multi-vector pitch-orthogonal LPC: quality speech
with low complexity at rates between 4 and 8 kbps,” ICSLP, Kobe, pp. 113-116, 1990. 3. MA …