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This paper presents the implementation of two nonlinear noise reduction methods applied to speech en...
[[abstract]]In this article, we present an effective compensation scheme to improve noise robustness...
Nonlinearity compensation in digital coherent receivers is feasible from a fundamental point of view...
The performance, reliability, and ubiquity of automatic speech recognition systems has flourished in...
The performance, reliability, and ubiquity of automatic speech recognition systems has flourished in...
In this paper, an algorithm to blindly compensate zero-memory nonlinear distortions of speech wavefo...
Automatic speech recognition has a wide variety of uses in this technological age, yet speech distor...
This paper presents the implementation of two nonlinear noise reduction methods applied to speech en...
Abstract—In this paper, we present the Gauss-Newton method as a unified approach to estimating noise...
Model compensation is a standard way of improving the robustness of speech recognition systems to no...
UnrestrictedThis dissertation shows how noise can benefit nonlinear signal processing. These "stocha...
In this paper, we present the Gauss-Newton method as a unified ap-proach to optimizing non-linear no...
The paper presents the implementation of two nonlinear noise reduction methods applied to speech enh...
This paper proposes a noise-biased compensation of minimum statistics (MS) method using a nonlinear ...
Compensation of nonlinear distortions is an issue of importance for the restoration of degraded audi...
This paper presents the implementation of two nonlinear noise reduction methods applied to speech en...
[[abstract]]In this article, we present an effective compensation scheme to improve noise robustness...
Nonlinearity compensation in digital coherent receivers is feasible from a fundamental point of view...
The performance, reliability, and ubiquity of automatic speech recognition systems has flourished in...
The performance, reliability, and ubiquity of automatic speech recognition systems has flourished in...
In this paper, an algorithm to blindly compensate zero-memory nonlinear distortions of speech wavefo...
Automatic speech recognition has a wide variety of uses in this technological age, yet speech distor...
This paper presents the implementation of two nonlinear noise reduction methods applied to speech en...
Abstract—In this paper, we present the Gauss-Newton method as a unified approach to estimating noise...
Model compensation is a standard way of improving the robustness of speech recognition systems to no...
UnrestrictedThis dissertation shows how noise can benefit nonlinear signal processing. These "stocha...
In this paper, we present the Gauss-Newton method as a unified ap-proach to optimizing non-linear no...
The paper presents the implementation of two nonlinear noise reduction methods applied to speech enh...
This paper proposes a noise-biased compensation of minimum statistics (MS) method using a nonlinear ...
Compensation of nonlinear distortions is an issue of importance for the restoration of degraded audi...
This paper presents the implementation of two nonlinear noise reduction methods applied to speech en...
[[abstract]]In this article, we present an effective compensation scheme to improve noise robustness...
Nonlinearity compensation in digital coherent receivers is feasible from a fundamental point of view...