Masking threshold

About: Masking threshold is a research topic. Over the lifetime, 391 publications have been published within this topic receiving 6611 citations.

Transform coding of audio signals using perceptual noise criteria

Abstract: A 4-b/sample transform coder is designed using a psychoacoustically derived noise-making threshold that is based on the short-term spectrum of the signal. The coder has been tested in a formal subjective test involving a wide selection of monophonic audio inputs. The signals used in the test were of 15-kHz bandwidth, sampled at 32 kHz. The bit rate of the resulting coder was 128 kb/s. The subjective test shows that the coded signal could not be distinguished from the original at that bit rate. Subsequent informal work suggests that a bit rate of 96 kb/s may maintain transparency for the set of inputs used in the test. >

Digital watermarks for audio signals

Abstract: In this paper, we present a novel technique for embedding digital "watermarks" into digital audio signals. Watermarking is a technique used to label digital media by hiding copyright or other information into the underlying data. The watermark must be imperceptible and should be robust to attacks and other types of distortion. In addition, the watermark also should be undetectable by all users except the author of the piece. In our method, the watermark is generated by filtering a PN-sequence with a filter that approximates the frequency masking characteristics of the human auditory system (HAS). It is then weighted in the time domain to account for temporal masking. We discuss the detection of the watermark and assess the robustness of our watermarking approach to attacks and various signal manipulations.

Single channel speech enhancement based on masking properties of the human auditory system

Abstract: This paper addresses the problem of single channel speech enhancement at very low signal-to-noise ratios (SNRs) (<10 dB). The proposed approach is based on the introduction of an auditory model in a subtractive-type enhancement process. Single channel subtractive-type algorithms are characterized by a tradeoff between the amount of noise reduction, the speech distortion, and the level of musical residual noise, which can be modified by varying the subtraction parameters. Classical algorithms are usually limited to the use of fixed optimized parameters, which are difficult to choose for all speech and noise conditions. A new computationally efficient algorithm is developed based on masking properties of the human auditory system. It allows for an automatic adaptation in time and frequency of the parametric enhancement system, and finds the best tradeoff based on a criterion correlated with perception. This leads to a significant reduction of the unnatural structure of the residual noise. Objective and subjective evaluation of the proposed system is performed with several noise types form the Noisex-92 database, having different time-frequency distributions. The application of objective measures, the study of the speech spectrograms, as well as subjective listening tests, confirm that the enhanced speech is more pleasant to a human listener. Finally, the proposed enhancement algorithm is tested as a front-end processor for speech recognition in noise, resulting in improved results over classical subtractive-type algorithms.

Optimizing digital speech coders by exploiting masking properties of the human ear

Abstract: In any speech coding system that adds noise to the speech signal, the primary goal should not be to reduce the noise power as much as possible, but to make the noise inaudible or to minimize its subjective loudness. ’’Hiding’’ the noise under the signal spectrum is feasible because of human auditory masking: sounds whose spectrum falls near the masking threshold of another sound are either completely masked by the other sound or reduced in loudness. In speech coding applications, the ’’other sound’’ is, of course, the speech signal itself. In this paper we report new results of masking and loudness reduction of noise and describe the design principles of speech coding systems exploiting auditory masking.

Method of transmitting or storing masked sub-band coded audio signals

Abstract: In the transmission of audio signals, the audio signal is digitally represented by use of quadrature mirror filtering in the form a plurality of spectral sub-band signals. The quantizing of the sample values in the sub-bands, e.g. 24 sub-bands, is controlled to the extent that the quantizing noise levels of the individual sub-band signals are at approximately the same level difference from the masking threshold of the human auditory system resulting from the individual sub-band signals. The differences of the quantizing noise levels of the sub-band signals with respect to the resulting masking threshold are set by the difference between the total information flow required for coding and the total information flow available for coding. The available total information flow is set and may then fluctuate as a function of the signal.