In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...

In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...

Traditionally, cerebellar model articulation controller (CMAC) is used in motor control, inverted pendulum robot, and nonlinear channel equalization. In this study, we investigate the capability of CMAC for speech enhancement. We construct a CMAC-based supervised speech enhancement system, which includes offline and online phases. In the offline phase, a paired noisy-clean speech dataset is pre...

In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...

This paper proposes a novel speech recognition method combining Audio-Visual Voice Activity Detection (AVVAD) and Audio-Visual Automatic Speech Recognition (AVASR). AVASR has been developed to enhance the robustness of ASR in noisy environments, using visual information in addition to acoustic features. Similarly, AVVAD increases the precision of VAD in noisy conditions, which detects presence ...

This paper presents a new method to detect speech/nonspeech components of a given noisy signal. Employing the combination of binaryWalsh basis functions and an analysis-synthesis scheme, the original noisy speech signal is modified first. From themodified signals, the speech components are distinguished from the nonspeech components by using a simple decision scheme. Minimal number of Walsh bas...

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...

In this Thesis two wavelet based methods (TADWT and SSWPT) for enhancement of noisy speech are developed and reported. The effectiveness of the reported speech enhancement techniques is evaluated by means of speaker recognition under noisy conditions. The automatic speaker recognition technologies have been developed into more and more important modern technologies required by many speech-aided...

An effective way to increase noise robustness in automatic speech recognition (ASR) systems is feature enhancement based on an analytical distortion model that describes the effects of noise on the speech features. One of such distortionmodels that has been reported to achieve a good trade-off between accuracy and simplicity is the masking model. Under this model, speech distortion caused by en...

Most compensation methods to improve the robustness of speech recognition systems in noisy environments such as spectral subtraction, CMN, and MVN, rely on the fact that noise and speech spectra are independent. However, the use of limited window in signal processing may introduce a cross-term between them, which deteriorates the speech recognition accuracy. To tackle this problem, we introduce...