Spoken language recognition refers to the automatic process through which we determine
or verify the identity of the language spoken in a speech sample. We study a computational …

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 …

Abstract Convolutional Neural Networks (CNNs) are an alternative type of neural network
that can be used to reduce spectral variations and model spectral correlations which exist in …

This paper examines the application of linear transformations for speaker and environmental
adaptation in an HMM-based speech recognition system. In particular, transformations that …

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 …

We present a structured overview of adaptation algorithms for neural network-based speech
recognition, considering both hybrid hidden Markov model/neural network systems and end …

A complete overview of distant automatic speech recognition The performance of
conventional Automatic Speech Recognition (ASR) systems degrades dramatically as soon …

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 …

In this paper, we propose a new fast speaker adaptation method for the hybrid NN-HMM
speech recognition model. The adaptation method depends on a joint learning of a large …

We present a method to derive Mel-frequency cepstral coefficients directly from the power
spectrum of a speech signal. We show that omitting the filterbank in signal analysis does not …