A Non-Intrusive Quality and Intelligibility Measure of Reverberant and Dereverberated Speech

Falk, Tiago H.; Zheng, Chenxi; Chan, Wai-Yip

doi:10.1109/tasl.2010.2052247

Cited by 316 publications

(228 citation statements)

References 30 publications

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“…Focus is placed on hands-free speech communications where reverberation can severely degrade the signal timbre [11,12], cause temporal smearing, and ultimately degrade speech quality and intelligibility [13]. Here, two reverberant environments are considered: a home living room and a large auditorium.…”

Section: Introductionmentioning

confidence: 99%

Cognitive, affective, and experience correlates of speech quality perception in complex listening conditions

Voigt-Antons

Laghari

Arndt

et al. 2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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Subjective speech quality assessment depends on listener "quality" opinions after hearing a particular test speech stimulus. Subjective scores are given based on a perception and quality judgment process that is unique to a particular listener. These processes are postulated to be dependent on the listener's internal reference of what good and bad quality sounds like, as well as their mental and emotional states. To overcome this variability, subjective listening tests often average scores over several listeners. In this paper, we use electroencephalography (EEG) and self-assessment tools to investigate the neural and affective correlates of speech quality perception of reverberant speech, with the goal of obtaining new insights into human speech quality perception in complex listening environments. We show that EEG event related potentials (ERP) are a useful tool to monitor the conscious stages of neural-processing during a speech quality assessment task. Significant correlations were obtained between the so-called P300 ERP component and the reverberation time of the room, as well as between the P300 peak amplitude and emotional self-assessment ratings. These insights could lead to more effective ways of characterizing room acoustics for improved speech quality and intelligibility.

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Section: Introductionmentioning

confidence: 99%

Cognitive, affective, and experience correlates of speech quality perception in complex listening conditions

Voigt-Antons

Laghari

Arndt

et al. 2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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“…This feature exploits the modulation spectral characteristics of clean speech to compare the modulation energy between the signal and the "room reverberation". In the context of the original feature definition, an additional noise was found to be caused by room reverberation (Falk et al, 2010). For TE speech, it was shown in (Huang et al, 2009) that these additional modulation frequencies are due to artefacts (e.g.…”

Section: Gargling Noise/creakinessmentioning

confidence: 99%

“…Another feature characterizing the gargling noise present in the voice is the reverberation-to-signal modulation energy ratio (RSMR), originally introduced in (Falk et al, 2010). This feature exploits the modulation spectral characteristics of clean speech to compare the modulation energy between the signal and the "room reverberation".…”

Section: Gargling Noise/creakinessmentioning

confidence: 99%

Tracheoesophageal speech: A dedicated objective acoustic assessment

Drugman

Rijckaert²,

Janssens³

et al. 2015

Computer Speech & Language

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“…Another approach was proposed in [8], based on the modulation spectrogram, that is, the spectrum of the temporal envelope computed in each frequency band. The principle is that the modulation energy is concentrated around 4 Hz for clean signals and tends to spread towards high modulation frequencies in case of reverberation.…”

Section: Introductionmentioning

confidence: 99%

An image-inspired audio sharpness index

Mahé

Moisan

Mitrea

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-We propose a new non-intrusive (reference-free) objective measure of speech intelligibility that is inspired from previous works on image sharpness. We define the audio Sharpness Index (aSI) as the sensitivity of the spectrogram sparsity to the convolution of the signal with a white noise, and we calculate a closed-form formula of the aSI. Experiments with various speakers, noise and reverberation conditions show a high correlation between the aSI and the well-established Speech Transmission Index (STI), which is intrusive (full-reference). Additionally, the aSI can be used as an intelligibility or clarity criterion to drive sound enhancement algorithms. Experimental results on stereo mixtures of two sounds show that blind source separation based on aSI maximization performs well for speech and for music.

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A Non-Intrusive Quality and Intelligibility Measure of Reverberant and Dereverberated Speech

Cited by 316 publications

References 30 publications

Cognitive, affective, and experience correlates of speech quality perception in complex listening conditions

Cognitive, affective, and experience correlates of speech quality perception in complex listening conditions

Tracheoesophageal speech: A dedicated objective acoustic assessment

An image-inspired audio sharpness index

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