• Speech Sciences
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• v.6
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• pp.163-179
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• 1999

For the set up, management and repair of a mobile communication system, continuous estimation of speech quality is required. Speech quality measurement can be conducted by listener's judgement in a subjective test such as MOS (Mean Opinion Score) test. However, this method is laborious, expensive and time-consuming, it is advisable to predict subjective speech quality via objective measures. This paper presents a robust objective speech quality measure, PLP-CMS (Perceptual Linear Predictive-Cepstral Mean Subtraction), which can predict subjective speech quality in mobile communication systems. PLP-CMS has a high correlation with subjective quality owing to PLP (Perceptual Linear Predictive) analysis and shows a robust performance not being influenced by PSTN (Public Switched Telephone Network) channel effects due to CMS (Cepstral Mean Subtraction). To prove the performance of our proposed algorithm, we carried out subjective and objective quality estimation on speech samples which are variously distorted in a real mobile communication system. As a result, we demonstrated that PLP-CMS has a higher correlation with subjective quality than PSQM (Perceptual Speech Quality Measure) and PLP-CD (Perceptual Linear Predictive-Cepstral Distance).

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.53-58
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• 2001

In this paper to develop objective speech quality measure for CDMA telephone network environments, recent developed measures are investigated first. But those measures show low performances in CDMA telephone networks. To solve this problem, new objective speech quality measure adopting noise masking threshold is proposed and studied. To acquire better performance, scaled noise masking threshold calculation for speech signals is employed instead of conventional tone signals. To verify effectiveness of proposed method performance comparison experiments are carried out for CDMA telephone network speech databases, for the results proposed methods show improved performances compared to existing meaures.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.71-75
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• 2010

The PESQ is an objective speech quality evaluation measure that is known to have a high correlation with a subjective speech quality measure such as MOS. To examine whether it could be useful as an objective quality measure of synthetic speech, we carried out both subjective evaluation tests with MOS and DMOS and an objective evaluation test with PESQ for HMM-based Korean synthetic speech signals and analyzed the correlation between them. Experimental results have shown that the PESQ has correlations of 0.87 with MOS and 0.92 with DMOS. It means that the PESQ holds much promise for evaluating the quality of synthetic Korean speech.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.405-414
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• 2002

In this paper, we propose a new objective speech quality measure using noise masking threshold for speech quality assessment of mobile telephone network environments, and verify the effectiveness of the proposed method through the experiments. For such a purpose, well known objective speech quality measures such as BSD and PSQM are first evaluated for digital mobile telephone network environments. However, these conventional methods does not have good performance under mobile networks environments compared to literary results. To be mote effective objective speech quality measure under mobile telephone environments, the proposed method employs human psychoacoustic masking effect. The DMOS, instead of MOS, is used as a subjective speech quality measure for performance evaluation. The performance comparison are carried out with speech data collected from digital mobile telephone environments. As results, the proposed measure have and average 4% higher performance, in terms of correlation, than existing objective speech quality measures such as BSD and PSQM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2291-2297
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• 2017

This paper describe to extract speech measure algorithm for evaluating a speech database, and presents generating method of a speech quality measure using DNN(Deep Neural Network). In our previous study, to produce an effective speech quality measure, we propose a combination of various speech measures which are highly correlated with WER(Word Error Rate). The new combination of various types of speech quality measures in this study is more effective to predict the speech recognition performance compared to each speech measure alone. In this paper, we describe the method of extracting measure using DNN, and we change one of the combined measure from GMM(Gaussican Mixture Model) score used in the previous study to DNN score. The combination with DNN score shows a higher correlation with WER compared to the combination with GMM score.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.464-470
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• 2016

This paper presents a speech recognition database verification system using speech measures, and describes a speech measure extraction algorithm which is applied to this system. In our previous study, to produce an effective speech quality measure for the system, we propose a combination of various speech measures which are highly correlated with WER (Word Error Rate). The new combination of various types of speech quality measures in this study is more effective to predict the speech recognition performance compared to each speech measure alone. In this paper, we increase the system independency by employing GMM acoustic score instead of HMM score which is obtained by a secondary speech recognition system. The combination with GMM score shows a slightly lower correlation with WER compared to the combination with HMM score, however it presents a higher relative improvement in correlation with WER, which is calculated compared to the correlation of each speech measure alone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.471-476
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• 2016

This paper presents our study on speech recognition performance prediction. Our initial study shows that a combination of speech quality measures effectively improves correlation with Word Error Rate (WER) compared to each speech measure alone. In this paper we demonstrate a new combination of various types of speech quality measures shows more significantly improves correlation with WER compared to the speech measure combination of our initial study. In our study, SNR, PESQ, acoustic model score, and MFCC distance are used as the speech quality measures. This paper also presents our speech database verification system for speech recognition employing the speech measures. We develop a WER prediction system using Gaussian mixture model and the speech quality measures as a feature vector. The experimental results show the proposed system is highly effective at predicting WER in a low SNR condition of speech babble and car noise environments.

• Phonetics and Speech Sciences
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• v.6 no.1
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• pp.71-76
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• 2014

In this paper voice quality of normal speech is qualitatively classified by five components of breathy, creaky, rough, nasal, and thin/thick voice. To determine whether a correlation exists between a subjective measure of voice and an objective measure of voice, each voice is perceptually evaluated using the 1/2/3 scale by speech processing specialists and acoustically analyzed using speech analysis tools such as the Praat, MDVP, and VoiceSauce. The speech parameters include features related to speech source and vocal tract filter. Statistical analysis uses a two-independent-samples non-parametric test. Experimental results show that statistical analysis identified a significant correlation between the speech feature parameters and the components of voice quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.881-890
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• 1992

Resonable speech quality assessment methodologies are required for speech quality assessment model which is used at speech system and communication network. There are objectlve measuies and subjective measures and subjective measure has the variousproblems in speech quality assessment methodologies. The objective of this study is to compare objective measures with subjective measure and obtain the objective measure as close as possible to subjective measure.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.42-49
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• 1993

In this paper, we evaluate the quality of synthesized speech by rule using the LPC CD as a objective measure, and then compare the test result with the subjective one. Speech used for the test consists of 108 words which are selected by word construction method using Korean attribute and frequency distribution, synthesized by demi-syllable rule. By evaluating the quality of synthesized speech by reule objectively, we have tried to resolve the problems such as lots of evaluation time, expansion of test scale, and variables of analysis result arised by subjective measure. We have, also, proved the validity of the objective test using the LPC CD, by comparing intelligibility which is the index for the subjective quality evaluation of synthesized speech by rule with MOS. From this results, we can provide a guide for quality assessment that would be useful in the R&D of synthesis method and the commercial products using synthesized speech.