This paper describes initial work on two of these problems: efficient multi-class classification; and training SVMs where no examples of the word are available.
Abstract: Using discriminative classifiers, such as Support Vector Machines (SVMs) in combination with, or as an alternative to, Hidden Markov Models (HMMs) ...
In this paper, we have compared two approaches in noisy environments: first, a hybrid HMM–SVM solution where a fixed number of frames is selected by means of ...
PDF | The improved theoretical properties of Support Vector Machines with respect to other machine learning alternatives due to their max-margin.
This paper examines one form of these models, structured support vector machines (SVMs), for noise robust speech recognition. One important aspect of structured ...
Missing: ASR. | Show results with:ASR.
In this paper, we have compared two approaches in noisy environments: first, a hybrid HMM–SVM solution where a fixed number of frames is selected by means of an ...
This paper has examined the use of structured SVMs for noise robust ASR. One key part of this work, compared to previ- ous work, is that the alignment of ...
People also ask
Is SVM robust to noise?
Is support vector machine outdated?
What is the support vector in SVR?
What are support vector machines good for?
The improved theoretical properties of Support Vector Machines with respect to other machine learning alternatives due to their max-.
This paper proposes robust noise automatic speaker identification (ASI) scheme named MKMFCC---SVM. It based on the Multiple Kernel Weighted Mel Frequency ...
Missing: ASR. | Show results with:ASR.
This paper examines one form of these models, structured support vector machines (SVMs), for noise robust speech recognition. ... Conclusion This paper has ...