This paper deals with measurements of the combined effect of signal strength and background traffic load on speech quality in IEEE 802.11 WLAN. The ITU-T G.729AB encoding scheme is deployed in this study and the Distributed Internet Traffic Generator (D-ITG) is used for the purpose of background traffic generation. The speech quality and background traffic load are assessed by means of the acco...

The effect of ideal time-frequency masking (ITFM) on the intelligibility of reverberated speech is tested using objective measurement, namely STI and PESQ scores. The best choice of ITFM threshold is determined for a range of reverberation times (RTs). Four existing dereverberation algorithms are also assessed. Objective test results and informal subjective listening show that IFTM provides gre...

Abstract Speech is easily interfered by external environment in reality, which results the loss of important features. Deep learning has become a popular speech enhancement method because its superior potential solving nonlinear mapping problems for complex However, deficiency traditional deep methods weak capability information from previous time steps and long-term event dependencies between ...

This study proposes a cross-domain multi-objective speech assessment model, called MOSA-Net, which can simultaneously estimate the quality, intelligibility, and distortion scores of an input signal. MOSA-Net comprises convolutional neural network bidirectional long short-term memory architecture for representation extraction, multiplicative attention layer fully connected each metric prediction...

The speech signal enhancement is essential to obtain clean speech signal from noisy signal. For multimodal optimization, the natural-inspired algorithms such as Firefly Algorithm (FA) are better. The proposed algorithm contains preprocessing module, optimization module and spectral filtering module. Here, Loizou’s and Aurora databases are considered for signals. In this paper the Perceptional E...

It is essential to ensure a satisfactory QoS (Quality of Service) when offering a speech communication system with a noise reduction algorithm. In this paper, we propose a new obejective test methodology for noise-reduced speech that estimates word intelligibility by using a distortion measure. Experimental results confirmed that the proposed methodology gives an accurate estimate with independ...

This paper presents a low-complexity pitch estimation algorithm for packet loss concealment. The algorithm divides the pitch estimation into three stages with each additional stage providing further accuracy. Compared with a system based on G.711 Appendix I, the proposed algorithm requires approximately 32 percent fewer cycles on a DSP processor integrated in a Bluetooth chip. Furthermore, obje...

Abstract Estimating time-frequency domain masks for single-channel speech enhancement using deep learning methods has recently become a popular research field with promising results. In this paper, we propose novel components loss (CL) the training of neural networks mask-based enhancement. During process, proposed CL offers separate control over preservation component quality, suppression nois...

To ensure a satisfactory QoE (Quality of Experience) and facilitate system design in speech recognition services, it is essential to establish a method that can be used to efficiently investigate recognition performance in different noise environments. Previously, we proposed a performance estimation method using the PESQ (Perceptual Evaluation of Speech Quality) as a measure of speech distorti...