Major progress is being recorded regularly on both the technology and exploitation of
automatic speech recognition (ASR) and spoken language systems. However, there are still …

Over the past decade or so, several advances have been made to the design of modern
large vocabulary continuous speech recognition (LVCSR) systems to the point where their …

We investigate the potential of Context-Dependent Deep-Neural-Network HMMs, or CD-
DNN-HMMs, from a feature-engineering perspective. Recently, we had shown that for …

The Application of Hidden Markov Models in Speech Recognition Page 1 The Application of
Hidden Markov Models in Speech Recognition Full text available at: http://dx.doi.org/10.1561/2000000004 …

This thesis investigates the use of discriminative criteria for training HMM parameters for
speech recognition, in particular the Maximum Mutual Information (MMI) criterion and a new …

We carry out an in-depth investigation on a newly proposed Maximum F1-score Criterion
(MFC) discriminative training objective function for Goodness of Pronunciation (GOP) based …

A language model (LM) is calculated as the probability of a word sequence that provides the
solution to word prediction for a variety of information systems. A recurrent neural network …

This paper examines how people communicate with computers using speech. Automatic
speech recognition (ASR) transforms speech into text, while automatic speech synthesis [or …

This paper describes the speech activity detection (SAD) system developed by the Patrol
team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) …

We introduce a method for deriving a metric, locally based on the Fisher information matrix,
into the data space. A self-organizing map (SOM) is computed in the new metric to explore …