Add to ORKGAbstract In this paper, Linear Discriminant Analysis (LDA) is investigated with respect to the combination of different acoustic features for automatic speech recognition. It is shown that the combination of acoustic features using LDA does not consistently lead to improvements in word error rate. A detailed analysis of the recognition results on the Verbmobil (VM II) and on the English portion of the European Parliament Plenary Sessions (EPPS) corpus is given. This includes an independent analysis of the effect of the dimension of the input to LDA, the effect of strongly correlated input features, as well as a detailed numerical analysis of the generalized eigenvalue problem underlying LDA. Relative improvements in word error rate of up to...
A general approach for integrating different acoustic fea-ture sets and acoustic models is presented...
A general approach for integrating different acoustic fea-ture sets and acoustic models is presented...
[[abstract]]© 2004 Institute of Electrical and Electronics Engineers - When a speech signal is encod...
In this thesis, the use of multiple acoustic features of the speech signal is considered for speech ...
Linear discriminant analysis (LDA) is designed to seek a linear transformation that projects a data ...
148 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.In the second part of this wo...
We have recently proposed a new acoustic model based on prob-abilistic linear discriminant analysis ...
The aim of discriminant feature analysis techniques in the signal processing of speech recognition s...
We have recently proposed a new acoustic model based on prob-abilistic linear discriminant analysis ...
The speaker recognition task falls under the general problem of pattern classification. Speaker reco...
Mel-Frequency Cepstral Coefficients and their derivatives are commonly used as acoustic features for...
Linear discriminant analysis (LDA) is a simple and effective feature transformation technique that a...
Linear discriminant analysis (LDA) is a simple and effective feature transformation technique that a...
this report the problem is to accurately detect the 48 phonemes in the English language and hence, o...
Several speech processing and audio data-mining applications rely on a description of the acoustic e...
A general approach for integrating different acoustic fea-ture sets and acoustic models is presented...
A general approach for integrating different acoustic fea-ture sets and acoustic models is presented...
[[abstract]]© 2004 Institute of Electrical and Electronics Engineers - When a speech signal is encod...
In this thesis, the use of multiple acoustic features of the speech signal is considered for speech ...
Linear discriminant analysis (LDA) is designed to seek a linear transformation that projects a data ...
148 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.In the second part of this wo...
We have recently proposed a new acoustic model based on prob-abilistic linear discriminant analysis ...
The aim of discriminant feature analysis techniques in the signal processing of speech recognition s...
We have recently proposed a new acoustic model based on prob-abilistic linear discriminant analysis ...
The speaker recognition task falls under the general problem of pattern classification. Speaker reco...
Mel-Frequency Cepstral Coefficients and their derivatives are commonly used as acoustic features for...
Linear discriminant analysis (LDA) is a simple and effective feature transformation technique that a...
Linear discriminant analysis (LDA) is a simple and effective feature transformation technique that a...
this report the problem is to accurately detect the 48 phonemes in the English language and hence, o...
Several speech processing and audio data-mining applications rely on a description of the acoustic e...
A general approach for integrating different acoustic fea-ture sets and acoustic models is presented...
A general approach for integrating different acoustic fea-ture sets and acoustic models is presented...
[[abstract]]© 2004 Institute of Electrical and Electronics Engineers - When a speech signal is encod...