Although there are numerous papers describing single-channel noise reduction strategies to improve speech perception in a noisy environment, few studies have comprehensively evaluated the effects of noise reduction algorithms on speech quality for hearing impaired (HI). A model-based sparse coding shrinkage (SCS) algorithm has been developed, and has shown previously (Sang et al., 2014) that it...

Problem statement: Speech corpus is one of the major components in corpus-based synthesis. The quality and coverage in speech corpus will affect the quality of synthesis speech sound. Approach: This study proposes a corpus design for Malay corpus-based speech synthesis system. This includes the study of design criteria in corpus-based speech synthesis, Malay corpus based database design and the...

In a competitive telecommunication market where price differentials have been minimized, quality of service (QoS) has become very important. Speech quality is a major dimension of perceived QoS, and the ability to monitor and design for this quality is a top priority. Traditionally, the perceived quality of speech has been measured by expensive and time-consuming subjective listening tests. Ove...

Speech Enhancement is a challenging and important area of research due to the many applications that depend on improved signal quality. It is a pre-processing step of speech processing systems and used for perceptually improving quality of speech for humans. With recent advances in Deep Neural Networks (DNN), deep Denoising Auto-Encoders have proved to be very successful for speech enhancement....

Recently, Quality of Experience (QoE) of voice service has been paid more attentions because it represents the performance of voice service subjectively perceived by the end users. And speech quality is commonly used to measure the QoE value. In this paper, a speech quality assessment algorithm is proposed for GSM network, aiming to predict and monitor QoE of voice service based on radio link p...

This paper presents an objective speech quality model, ViSQOL, the Virtual Speech Quality Objective Listener. It is a signal-based, full-reference, intrusive metric that models human speech quality perception using a spectro-temporal measure of similarity between a reference and a test speech signal. The metric has been particularly designed to be robust for quality issues associated with Voice...

Perceived conversational speech quality is a key quality of service (QoS) metric for voice over IP (VoIP) applications. Speech quality is mainly affected by network impairments, such as delay, jitter and packet loss. Playout buffer algorithms are used to compensate for jitter, based on a tradeoff between delay and loss, but can have a significant effect on perceived quality. The main aim in thi...