The generalized spectral subtraction algorithm (GBSS), which has extraordinary ability in background noise reduction, is historically one of the first approaches used for speech enhancement and dereverberation. However, not been applied to de-noise room impulse response (RIR) extend reverberation decay range. application GBSS this study stated as an optimization problem, that is, subtracting le...

An important problem in speaker recognition is the degradation that occurs when speaker models trained with speech from one type of channel are used to score speech from another type of channel, known as channel mismatch. This thesis investigates various channel compensation techniques and approaches from missing feature theory for improving Gaussian mixture model (GMM)-based speaker verificati...

Automatic Speech Recognition (ASR) has matured into a technology which is becoming more common in our everyday lives, and is emerging as a necessity to minimise driver distraction when operating in-car systems such as navigation and infotainment. In “noise-free” environments, word recognition performance of these systems has been shown to approach 100%, however this performance degrades rapidly...

We propose an overlapped speech detection method for speech recognition and speaker diarization of meetings, where each speaker wears a lapel microphone. Two novel features are utilized as inputs for a GMM-based detector. One is speech power after cross-channel spectral subtraction which reduces the power from the other speakers. The other is an amplitude spectral cosine correlation coefficient...

Spectrally correlated photon pairs can be used to improve the performance of long-range fiber-based quantum communication protocols. We present a source based on spontaneous parametric downconversion, which allows one to control spectral correlations within the entangled photon pair without spectral filtering by changing the pump-pulse duration or the characteristics of the coupled spatial mode...

Assessment of clean speech from a noisy speech signal has been a research topic for a long time. This research finds its variety of applications, which includes the present mobile communication also. The most important outcome of this research is the improved quality and reduced listening effort in the presence of an interfering noise signal. In this paper the performance of various noise reduc...

This paper considers the problem of training/testing mismatch in the context of speaker verification and, in particular, explores the application of missing feature theory in the case of additive white Gaussian noise corruption in testing. Missing feature theory allows for corrupted features to be removed from scoring, the initial step of which is the detection of these features. One method of ...