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ICASSP
2010
IEEE
13 years 5 months ago
Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models
Although research has previously been done on multilingual speech recognition, it has been found to be very difficult to improve over separately trained systems. The usual approa...
Lukas Burget, Petr Schwarz, Mohit Agarwal, Pinar A...
ICASSP
2011
IEEE
12 years 9 months ago
A simplified Subspace Gaussian Mixture to compact acoustic models for speech recognition
Speech recognition applications are known to require a significant amount of resources (memory, computing power). However, embedded speech recognition systems, such as in mobile p...
Mohamed Bouallegue, Driss Matrouf, Georges Linares
ICASSP
2010
IEEE
13 years 5 months ago
Subspace Gaussian Mixture Models for speech recognition
We describe an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure, and the means and mixture weights vary in a subspace of the...
Daniel Povey, Lukas Burget, Mohit Agarwal, Pinar A...
ICASSP
2011
IEEE
12 years 9 months ago
An investigation of subspace modeling for phonetic and speaker variability in automatic speech recognition
This paper investigates the impact of subspace based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based...
Richard C. Rose, Shou-Chun Yin, Yun Tang
ICPR
2006
IEEE
14 years 6 months ago
A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models
In this paper we propose a novel order-recursive training algorithm for kernel-based discriminants which is computationally efficient. We integrate this method in a hybrid HMM-bas...
Edin Andelic, Marcel Katz, Martin Schafföner,...