Acoustic backing-off as an implementation of missing feature theory

Acoustic backing-off as an implementation of missing feature theory

Acoustic backing-off was recently proposed as an operationalisa­ tion of missing feature theory for increased recognition robustness. Acoustic backing-off effectively removes the detrimental influence of outlier values from the local decisions in the Viterbi algorithm without any kind of explicit outlier detection. In the context of con­ nected digit recognition over telephone lines, it is show...

Chapter 6 : Acoustic Backing - off as an Implementation of Missing Feature Theory

In this paper, we discuss acoustic backing-off as a method to improve automatic speech recognition robustness. Acoustic backing-off aims to achieve the same objective as the marginalization approach of Missing Feature Theory: The detrimental influence of outlier values is effectively removed from the local distance computation in the Viterbi algorithm. The proposed method is based on one of the...

development and implementation of an optimized control strategy for induction machine in an electric vehicle

in the area of automotive engineering there is a tendency to more electrification of power train. in this work control of an induction machine for the application of electric vehicle is investigated. through the changing operating point of the machine, adapting the rotor magnetization current seems to be useful to increase the machines efficiency. in the literature there are many approaches wh...

Acoustic backing-off in the local distance computation for robust automatic speech recognition

In this paper we propose to introduce backing-off in the acoustic contributions of the local distance functions used during Viterbi decoding as an operationalisation of missing feature theory for increased recognition robustness. Acoustic backing-off effectively removes the detrimental influence of outlier values from the local decisions in the Viterbi algorithm. It does so without the need for...

Acoustic Backing-off in the Local Distance Computation for Robust Automatic Speech Recognition