Measurement of the Effects of Temporal Clipping on Speech Quality

Ding, Lijing; Radwan, Ayman; El-Hennawey, M.S.; Goubran, Rafik

doi:10.1109/tim.2006.876538

Cited by 18 publications

(7 citation statements)

References 9 publications

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“…speech quality as one of the parameter for the service quality provided to the users by operators. Therefore, several non-intrusive tools have also been implemented to predict the speech quality in a telephone conversation, such as algorithms that use clipping statistics [3], digital watermarking [4], GSM encoders [5] and optimized multi-sine signals [6], but also In-Service Nonintrusive Measurement Device [7]. Moreover, techniques for the discrimination between speech and voice-band data transmission in telephone systems have been explored [8].…”

mentioning

confidence: 99%

Discriminating Pathological Voice From Healthy Voice Using Cepstral Peak Prominence Smoothed Distribution in Sustained Vowel

Castellana

Carullo

Corbellini

et al. 2018

IEEE Trans. Instrum. Meas.

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This paper deals with Cepstral Peak Prominence Smoothed (CPPS) distribution and its descriptive statistics as possible indicators of vocal health status. 41 voluntary patients and 35 control subjects participated in the experiment: all of them followed the same protocol, which includes three repetitions of the sustained vowel /a/ simultaneously acquired with a microphone in air and a contact sensor, the perceptual assessment of voice quality and the videolaringoscopy examination. The fifth percentile and the standard deviation of CPPS distribution were the parameters included in the best logistic regression models for the microphone in air and the contact sensor, respectively. The selected CPPS parameters had a strong to good discrimination power: an Area Under Curve of 0.95 and 0.87 has been found for the microphone in air and for the contact sensor, respectively. For each CPPS parameter, the repeatability has been also estimated and the Monte Carlo method has been implemented for the uncertainty evaluation of the discrimination threshold. Furthermore, preliminary recommendations for better accuracy and repeatability of future studies are provided: analyses on the main CPPS influence quantities and on the effect of the frequency content of the signal spectrum on the CPPS parameters have been provided. Index TermsCepstral analyses, human voice, biomedical measurement, acoustic devices, reproducibility of results, Monte Carlo methods, uncertainty I. INTRODUCTION Traditionally, voice quality has been assesed using subjective tests, in which experts listen to live or recorded vocal signals and perceptually rate them. In order to overcome the subjectivity and the expensiveness of such methods and with the aim to find a less time-consuming tool, researchers started to analyze voice signals and to extract several parameters as indexes of different aspects of voice and voice-related issues.

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mentioning

confidence: 99%

Discriminating Pathological Voice From Healthy Voice Using Cepstral Peak Prominence Smoothed Distribution in Sustained Vowel

Castellana

Carullo

Corbellini

et al. 2018

IEEE Trans. Instrum. Meas.

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“…Also, it can be used to correctly distinguish between the audible and inaudible distortions and this has proven to be the best way of accurately predicting the audibility and annoyance level of complex distortions [29], [30]. Hence, speech quality measure with respect to more audio criteria can be indicated for speech enhancement mechanisms [13], [31].…”

Section: B Optimization Of Decision-directed Agementioning

confidence: 99%

A Decision-Directed Adaptive Gain Equalizer for Assistive Hearing Instruments

Chan

Low

Nordholm

et al. 2014

IEEE Trans. Instrum. Meas.

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Assistive hearing instruments have a significant impact on speech enhancement when the signal-to-noise ratio is low. These instruments are usually developed using the conventional adaptive gain equalizer (AGE), which has low computational complexity and low distortion in real-time speech enhancement. The conventional AGEs are intended to boost the speech segments of speech signals but they are incapable of suppressing noise segments. The overall speech quality of the assistive hearing instruments may be reduced, as the noise segments still cannot be filtered out. In this paper, a decisiondirected AGE is proposed for assistive hearing instruments. It aims to overcome the limitation of the conventional AGE, which is capable only of boosting speech segments in noisy speech but incapable of suppressing noise segments. The proposed approach simultaneously boosts the speech segments and suppresses noise segments in noisy speech. Experimental results with different types of real-world noise indicate that the proposed method achieves better speech quality than does the conventional AGE. The resulting method provides an improved functionality for assistive hearing instruments.Index Terms-Adaptive gain equalizer (AGE), assistive hearing instruments, heuristic algorithms, particle swarm optimization (PSO), perceptual evaluation of speech quality (PESQ), single channel filter, speech booster, speech enhancement.

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“…In order to detect such distortions, Aleinik and Matveev (2014) presented a histogram method to estimate the level of signal clipping. Ding et al (2006) investigated the effects of temporal clipping on perceived speech quality. They proposed a non-intrusive algorithm based on the clipping statistics to predict speech quality.…”

Section: Introductionmentioning

confidence: 99%