Objective Quality Evaluation Method for Noise-Reduced Speech

Egi, Noritsugu; Aoki, Hitoshi; Takahashi, Akihiro

doi:10.1093/ietcom/e91-b.5.1279

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…However, the PESQ method can give poor estimates for noise-reduced speech, as we reported in [2]. Egi et al recently proposed a full-reference objective quality evaluation method for noise-reduced speech and showed its effectiveness [3]. The other approach is the non-reference approach that uses only the input speech for extracting the acoustical features, such as unnaturalness of speech, noise annoyance, and temporal interruption of speech.…”

Section: Introductionmentioning

confidence: 97%

Non-reference Objective Quality Evaluation for Noise-Reduced Speech Using Overall Quality Estimation Model

Kasuya

Shinohara

Kitawaki

2010

IEICE Trans. Commun.

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SUMMARYThis paper describes non-reference objective quality evaluation for noise-reduced speech. First, a subjective test is conducted in accordance with ITU-T Rec. P.835 to obtain the speech quality, the noise quality, and the overall quality of noise-reduced speech. Based on the results, we then propose an overall quality estimation model. The unique point of the proposed model is that the estimation of the overall quality is done only using the previously estimated speech quality and noise quality, in contrast to conventional models, which utilize the acoustical features extracted. Finally, we propose a non-reference objective quality evaluation method using the proposed model. The results of an experiment with different noise reduction algorithms and noise types confirmed that the proposed method gives more accurate estimates of the overall quality compared with the method described in ITU-T Rec. P.563. key words: non-reference objective quality evaluation, noise-reduced speech, overall quality estimation model,

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Section: Introductionmentioning

confidence: 97%

Non-reference Objective Quality Evaluation for Noise-Reduced Speech Using Overall Quality Estimation Model

Kasuya

Shinohara

Kitawaki

2010

IEICE Trans. Commun.

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“…The subjective model is time-consuming and costs are too much, because it requires a number of subjects in accessing quality [6]. An objective quality assessment model is now in widespread use to access quality faster and at lower cost [6,7]. The parametric model belongs to the objective quality model that uses input metrics of physical parameters rather than waveforms.…”

Section: Introductionmentioning

confidence: 99%

Burst packet loss and enhanced packet loss‐based quality model for mobile voice‐over Internet protocol applications

Jung

Manzano

2014

IET Communications

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“…In general, noise-reduced speech is evaluated from the viewpoints of subjective quality and intelligibility. Steady progress has been made toward the objective estimation of subjective quality in recent years [1], [2]. However, researches for intelligibility have not yet been conducted.…”

Section: Introductionmentioning

confidence: 99%

Objective Estimation of Word Intelligibility for Noise-Reduced Speech

Kumakura

Kitawaki

2008

IEICE Transactions on Communications

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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 independence of noise reduction algorithms and noise types.

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Objective Quality Evaluation Method for Noise-Reduced Speech

Cited by 4 publications

References 3 publications

Non-reference Objective Quality Evaluation for Noise-Reduced Speech Using Overall Quality Estimation Model

Non-reference Objective Quality Evaluation for Noise-Reduced Speech Using Overall Quality Estimation Model

Burst packet loss and enhanced packet loss‐based quality model for mobile voice‐over Internet protocol applications

Objective Estimation of Word Intelligibility for Noise-Reduced Speech

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