We present simultaneous spectroscopic observations taken during four observing runs (1996 to 1999) of Hα, Hβ, Hǫ, Ca ii H & K, and Ca ii IRT lines of the chromospherically active binary BF Lyn. Both components have strong emission in the Hǫ, Ca ii H & K and Ca ii IRT lines and a strong filling-in of the Hα and Hβ lines have been observed after the application of the spectral subtraction techniq...

This paper presents a method for enhancing speech signals in the root cepstral domain, typically in conjunction with the cepstral subtraction technique. The effect of the processing is similar to the spectral sharpening method performed in the time domain, but with a much lower computational requirement when combined with cepstral subtraction and with better performance. The portions of the sig...

This paper proposes a speech processing system based on a model of the human auditory system and a noise reduction neural network with fast Fourier transform (FFT) amplitude and phase spectrums for noise reduction under background noise environments. The proposed system reduces noise signals by using the proposed neural network based on FFT amplitude spectrums and phase spectrums, then implemen...

In the framework of Gaussian mixture models (GMMs) [1], we present a new approach towards robust automatic speaker verification (SV) in adverse conditions. This new and simple approach is based on the combination of a speech enhancement using traditional spectral subtraction, and a missing feature compensation to dynamically modify the probability computations performed in GMM recognizers. The ...

In this paper, we have evaluated a noisy speech recognition method based on noise reduction and acoustic model adaptation, on the AURORA2 tasks. For noise reduction method, we employed two noise reduction methods. One is an Adaptive Sub-Band Spectral Subtraction (ASBSS) method which can vary noise subtraction rate according to SNR in frequency bands at each frame. The other is a Kalman filterin...

Algorithms for the suppression of acoustic noise in speech signals are generally Short-Time Spectral Amplitude (STSA) methods such as Spectral Subtraction. These methods have been effective at reducing or removing the background noise, but have a tendency (at low SNR) to add annoying artefacts, such as musical noise, and distortion of the speech signal. By employing an auditory model, psychoaco...