||To facilitate storage and transmission, lossy compression is usually used for audio signals despite the possible quality degradation. On the other hand, scaling down of transistor sizes makes audio processing chips more sensible to process defects and noises and result in erroneous audio. Aging effects may also result in adverse impacts on audio quality. These would make messages delivered mis-understood. This problem becomes more critical for internet of things applications where speech recognition is expected to play an important role. Fortunately, minor variations in audio are likely to be imperceptible due to human beings’ hearing insensitivity. This makes errors possibly still acceptable. The life time of audio chips can thus be extended. Therefore, one critical issue is how to effectively evaluate the acceptability of audio.|
In the literature there have been a number of accurate audio assessment methods developed. However, high computation complexity is required for these methods where long software execution time or unaffordable high hardware cost would be incurred. In this work, our goal is to develop an efficient audio acceptability evaluation method based on human beings’ hearing sensibility.
PEAQ (Perceptual Evaluation of Audio Quality) is one of the widely used audio quality assessment methods. In this work, we use PEAQ results to evaluate accuracy of the proposed methods and also evaluate the performance. Two efficient methods are proposed. Compared to PEAQ, both methods can reduce the software execution time by 94.24% and 77.27%, respectively. The first method can effectively assess output quality of faulty audio circuits — 82.33% accuracy for ordinary audio and even 92.42% for speech. This method is also easy to be implemented by hardware. The incurred hardware cost is only 3.98% with respect to commercial MP3 decoders. The second method is effective for compressed audio. 100% accuracy is achievable when the bandwidth of the reference audio is large enough. For faulty compressed audio, 80.80% accuracy can be achieved. Compared with the first proposed method, this method has higher hardware implementation complexity, and thus software implementation is preferred. Nevertheless, the hardware cost can be reduced if hardware in audio systems is used and investigated with the proposed method.