An Objective Metric of Human Subjective Audio Quality Optimized for a Wide Range of Audio Fidelities

Perceptual-based quality assessment for audio–visual services: A survey

“…Most notably PEAQ is shown to be unreliable for signals with large impairment resulting from low bitrate coding [10]. Furthermore, PEAQ is limited to a maximum of two channels.…”

“…The limitation of PEAQ up to a maximum of two channels was addressed by the development of an expert system to assist with an optimization of multichannel audio system [12]. Creusere et al [10,13] presented an energy equalization quality metric (EEQM), which can be used in predicting the audio quality for a wide range of impairments. Furthermore, a variable called the energy equalization threshold (EET), used in EEQM, can also be appended in PEAQ as a complementary model output variable (MOV) to give a more accurate quality prediction [14].…”

“…To the best of our knowledge, there is no audio quality metric designed to handle HE-AAC v1 or v2. In this paper, we concentrate on the energy equalization approach (EEA) proposed by Creusere et al [10,13,14,59], PEMO-Q proposed by Huber and Kollmeier. [60], as well as two other simple metrics: measuring normalizing block (MNB) [61] and mean structural similarity [62], and test their performance on audio quality assessment for the parametric coding scheme.…”

“…In addition, when adding this threshold T as an additional MOV in PEAQ, the authors concluded that the three-layer neural network in PEAQ is unnecessary. Therefore, a least-square procedure was used in finding an optimal linear weighting for each MOV to get a scalar value estimate of audio quality, and such simple linear weighting is less susceptible to over-training and thus likely to provide a more robust quality metric [10]. Furthermore, a minimax optimal MOV selection was proposed for finding the most suitable subsets within all the MOVs (11/5 original MOVs in PEAQ basic/advanced version+threshold T) to minimize a cost function: the maximum absolute error between the objective metric output and the subjective quality measurement.…”

A Temporally Varying Objective Audio Quality Metric

“…Unfortunately subjective testing is expensive and time consuming. To overcome this difficulty, objective quality metrics have been designed to mimic the outcome of subjective testing [2,3,4,5]. Current objective metrics give only a single score for an entire sequence, a methodology that is only effective under the assumption that the error and underlying audio sequence are both stationary.…”