Quality Of Audio Signal Research Articles

Integrated psychoacoustic active noise control and masking

The active noise control (ANC) algorithms are widely applied in noise-canceling headphones. However, the disadvantage of conventional ANC algorithms is the high computational cost from high order finite-impulse-response filter, which also leads to slower convergence. Subband ANC algorithms, which are based on the subband adaptive filter, are used to reduce computational complexity and to increase convergence rate. Moreover, noise cancellation performance decreases at the higher frequency due to the decreasing control zone. In headphones based application, perceptual quality of noise attenuation and target audio signal are important factors, and ANC algorithm must be designed to account for the psychoacoustic parameters. In this paper, we propose a new noise reduction approach in order to solve some existing ANC headphones problems, especially high-frequency noise reduction and perceptual quality of the playback sound. The proposed algorithm is a new approach of integrated psychoacoustic subband ANC and psychoacoustic masking. Psychoacoustic subband ANC achieves lesser computational cost than conventional subband ANC by using the psychoacoustic model to attenuate only audible noise components during music playback in the headphones. Proposed new integrated system is efficient for broadband noise attenuation. Psychoacoustic ANC reduces noise in the most sensitive frequency range for human’s hearing system, 0–4000 Hz, and masking operates in order to mask out residual and high-frequency noise. In additional, proposed noise reduction system reduces only audible noise components. The integrated ANC-masking system applied psychoacoustic analysis without producing artificial distortions to the music signal. Objective and subjective perceptual tests are evaluated for the proposed ANC-masking system with other subband ANC and masking algorithms. Results show the advantage of the proposed integrated system in the terms of the perceptual sound quality and high-frequency noise reduction.

Research on Objective Evaluation of Recording Audio Restoration Based on Deep Learning Network

There are serious distortion problems in the history audio and video data. In view of the characteristics of audio data repair, the intelligent technology of audio evaluation is explored. As the traditional audio subjective evaluation method requires a large number of personal to audition and evaluation, the tester’s subjective sense of hearing deviation and sample space data limited the impact of the accuracy of the experiment. Based on the deep learning network, this paper designs an objective quality evaluation system for historical audio and video data and evaluates the performance of the system and the audio signal quality from the perspective of feature extraction and network parameter selection. Experiments show that the system has good performance in this experiment; the predictive results and subjective evaluation of the correlation and dispersion indicators are good, up to 0.91 and 0.19.

An Effective Watermarking Method Based on Energy Averaging in Audio Signals

Methods based on discrete cosine transform (DCT) have been proposed for digital watermarking of audio signals; however, the watermark is often vulnerable to data compression and signal processing. This paper presents an effective audio watermarking method by energy averaging of DCT coefficients such that an audio signal with watermark is robust to data processing. The method is to divide an audio signal into segments by three parameters defining the segment length, the segment sequence of watermark location, and the frequency range of DCT coefficients for watermark location. An error correcting code is also integrated to improve audio signal quality after watermarking. Experimental results show that the method is robust to data compression and many other kinds of signal processing. No original signal is required for decoding the watermark. Comparison of watermarking performance with a recent work validates that the watermarking method has better audio quality and higher robustness.

Robust audio watermarking algorithm based on DWT using Fibonacci numbers

This paper presents a blind and robust audio watermarking algorithm developed based on Fibonacci numbers properties and the discrete wavelet transform (DWT) advantages. The method embeds watermark bits in the 6th level approximation subband of DWT at which there is less sensitivity of the human auditory system. The key idea is dividing the 6th level approximation coefficients into small frames and modifying their magnitude based on Fibonacci numbers and watermark bit values. The proposed watermarking method demonstrates a superior robustness against different common attacks (i.e., Gaussian noise addition, Low-pass filter, Resampling, Requantizing, MP3 compression, Amplitude scaling, Echo addition, Time shift, and Cropping). Compared to recently developed methods, the proposed algorithm is much more robust against the most common attacks with capacity as high as 686 bits per second. The results of PEAQ testing verify the quality of watermarked audio signal without significant perceptual distortion. The algorithm allows flexibility in audio watermark algorithm to achieve a balance between robustness and imperceptibility while the capacity is maintained constant by choosing various kinds of sequence.

Analyses of decimation filter stopband attenuation influence on subjective quality of audio signals

Analyses of decimation filter stopband attenuation influence on subjective quality of audio signals

Feature analysis of dysphonia speech for monitoring Parkinson's disease.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that has no known cure and no known prevention. Early detection is crucial in order to slow down the progress. In the past 10 years, interest in PD analysis has visibly increased. Speech impairment affects the majority of people with Parkinson's (PWP). New features and machine learning algorithms were proposed to help diagnose PD and to measure a patient's progress. Using sustained vowel /a/ recordings, we identified a more prominent set of Mel-Frequency Cepstral Coefficient (MFCC) and Intrinsic Mode Functions (IMF), and other parameters that can best represent the characteristics of Parkinson's dysphonia to assist with the diagnosis process. For higher quality audio signals, there is a visible difference in the higher MFCC coefficients, the wider spectrum bandwidth in the first four IMFs of PWP, and higher power intensity in the healthy subjects. We also found that even when the signals are downsampled into toll-quality, the distinguishable MFCC and IMF features were largely maintained. This enabled a whole possibility of providing telemedicine for PWP.

5. High Quality Audio Signal Processing for Music

5. High Quality Audio Signal Processing for Music

Audio Bandwidth Extension Based on Ensemble Echo State Networks with Temporal Evolution

The bandwidth limitation of wideband audio systems degrades the subjective quality and naturalness of audio signals. In this paper, a new method for blind bandwidth extension of wideband audio signals is proposed based on ensemble echo state network with temporal evolution. The high-frequency components in the band of $7 \sim 14 \text{kHz}$ are artificially restored only from the information in the wideband audio. For each region in the wideband feature space, a specific echo state network with recurrent structure is explored to dynamically model the local mapping relationship between wideband audio features and high-frequency spectral envelope. The transition process among regions is modeled by a hidden Markov model, and a network ensemble technique based on temporal evolution is used to fuse multiple echo state networks such that the high-frequency spectral envelope is estimated. Combining the high-frequency fine spectrum extended by spectral translation, the proposed method can effectively extend the wideband audio to super wideband. In addition, the proposed extension method is applied to the ITU-T G.729.1 wideband audio codec and is further evaluated in comparison with the ITU-T G.729.1 Annex E super-wideband audio codec and the hidden Markov model-based reference bandwidth extension method. Objective quality evaluation results indicate that the proposed method is preferred over the hidden Markov model-based reference bandwidth extension method in terms of log spectral distortion, cosh measure, and differential log spectral distortion. Further, the proposed method improves the auditory quality of the wideband audio and also gains a good performance in the subjective listening tests.

Review: Audio Noise Reduction Using Filters and Discrete Wavelet Transformation

Audio noise reduction using filters and Discrete Wavelet Transformation” our applications include noise propagation problem in industrial air handling systems, noise in aircrafts and tonal noise from electric power, as well as isolation of vibration from which noise is one kind of sound that is unexpected or undesired . The noise related problem can be divided into non-additive noise and additive noise. The non-additive noise includes multiplier noise and convolution noise, which can be transformed into additive noise throughhomomorphism transform. The additive noise includes periodical noise, pulse noise, and broadband noise related problems. There are many kinds of broadband noise, which may include heat noise, wind noise, quantization noise, and all kinds of random noise such as white noise and pink noise. In acoustics applications, noise from the surrounding environment severely reduces the quality ofspeech and audio signals. Therefore, basic linear are used to denoise the audio signals and enhance speech and audio signal quality. Our main objective is to reduce noise from system which is heavily dependent on the specific context and application. As, we want to increase the intelligibility or improve the overall speech perception quality. Such as SNR, PSNR, MSE and the Time to reduce the noise for noisy signals for removing noise.

능동스피커를 위한 네트워크기반 디지털 크로스오버

최근 IT기술의 진보에 힘입어 프로오디오분야에 IT기술이 접목된 혁신적인 제품이 개발되고 있다. DSP는 SR 오디오 장비의 고품질 오디오 신호를 처리하는 중요한 역할을 수행한다. IT기술과 디지털오디오기술의 융합은 프로 오디오산업 종사자들에게 새로운 사용자 경험을 제공한다. 본 논문에서는 능동스피커시스템을 위한 인터넷기술과 DSP기술이 접목된 디지털크로스오버를 소개한다. 본 논문에서 구현된 디지털크로스오버는 디지털오디오신호를 처리하기 위한 필터, 딜레이, 위상제어기능을 가지고 있으며, 크로스오버의 동작상태 모니터링과 다수의 파라미터를 제어하기 위해 인터넷 연결기능을 가진다. Nowadays, there are many innovative products in the pro-audio market thanks to advanced IT technology, DSP is very important technology to process high quality audio signal in SR(Sound Reinforcement) system. Digital audio technology that converged with IT technology can give new user-experience. In this paper, we present a new digital crossover system for active speakers using DSP and network technology. The prototype of crossover module consists of various audio process module such as filters, delay, phase controls and also it provides user to remote monitoring and remote control features by internet connection.

Control Approaches for Audio Signal Quality Improvement in the Developed Conference System Based on the Personal User Devices

The paper describes developed conference system based on the interaction between personal user mobile devices and administrator's PC. This system can be used instead of expensive, sophisticated equipment for conferences with the appropriate quality of audio signal. Analysis of different approaches and technics and final algorithms are presented. Phase modulation, gain reduction, spatial filtering, room modeling methods, and particularly AGC, AEQ, notch howling suppression, pitch shifting were taken as the basic elements of signal processing procedures. Practical realization of the final system is described as well. Main part of the tuning goes in automatic mode but there is a fine-tuning possibility for the users in the manual mode.

Potential and Limits of a High-Density Hemispherical Array of Loudspeakers for Spatial Hearing and Auralization Research

A hemispherical array of 196 independent loudspeakers has been constructed for laboratory research on spatial hearing, auralization, sound-field quality and spatial audio signal processing. The array of small loudspeakers is supported by a geodesic frame with a radius is 2.4 m. With this relatively high spatial density of sound sources, spatially quantized rendering of sound fields should be viable for a variety of applications, and this paper considers the potential and limits of this approach in relation to human spatial hearing capacities. The paper also considers the combined use of multiple loudspeakers for the rendering low-frequency components of sound sources in order to extend the low-frequency response of the system.

Miscommunication in general aviation: The influence of external factors on communication errors

Miscommunication in aviation remains a serious threat to safety. Factors such as pilots workload, quality of audio signal, accent of pilot or controller, English language proficiency of operator, and failure to use standard phraseology are all thought to contribute to communication errors. Hence, the aim of the present research was to investigate if a relationship existed between four known factors moderating communication and communication accuracy. Seventeen pilots completed a total of eight separate simulated flights (presented in counterbalanced order), which were arranged in four flight pairings and the percentage of accurate transmissions were compared between each flight pairing. The results revealed that requiring four or more items in one radio transmission degraded communication performance. Similar results were noted when pilots were under high workloads. Eliminating prosodic features such as pauses in radio transmissions also increased communication errors; most notably for pilots whose native language was not English. There was no effect of airways congestion on pilot communication performance. The results are discussed from a theoretical and applied perspective.

Real-time audio steganography attack based on automatic objective quality feedback

Digital audio signal provides a large capacity for embedding hidden messages using digital steganography techniques. How to prevent hazardous steganography embedding on the Internet becomes an important task in the field of network security. For the Internet environment, the steganography attack method is required to be generic and real time. An active warden-based attack method is potential to be a generic method for the steganography attack. A discrete spring transform (DST)-based generic active warden steganography attack framework has been proposed by us. In this paper, based on the DST, a real-time steganography attack method is proposed. The potential unauthorized hidden message is removed in a real-time manner when uploading or downloading the audio signal. The real-time signal perceptual quality control is achieved by the automatic feedback from the objective audio quality evaluation model. The attack parameters are adaptively changed to reach a balance between the attack performance and the audio signal quality. The simulation results validate the proposed method in terms of the steganography attack performance and the audio signal quality after the attack. Copyright © 2014 John Wiley & Sons, Ltd.

A blind bandwidth extension method for audio signals based on phase space reconstruction

Bandwidth extension is an effective technique for enhancing the quality of audio signals by reconstructing their high-frequency components. In this paper, a novel blind bandwidth extension method is proposed based on phase space reconstruction. Phase space reconstruction is introduced to convert the low-frequency modified discrete cosine transform coefficients of wideband audio to a multi-dimensional space, and the high-frequency modified discrete cosine transform coefficients of the audio signal are reconstructed by a non-linear prediction model. The performance of the proposed method was evaluated through objective and subjective tests. It is found that the proposed method achieves a better performance than the typical linear extrapolation method, and its performance is comparable to the conventional efficient high-frequency bandwidth extension method.

음질 평가법의 표준과 연구 동향 - 전송 처리음 분야

음질 평가는 좋은 소리를 만들기 위해 필수적인 요소이며, 음향의 특성과 대상 시스템에 따라 다양한 방법이 사용되고 있다. 본 논문에서는 음질 평가법의 전반적인 방법론 및 전송 처리된 음향 신호의 품질 평가법에 대해 ITU-T, ITU-R, IEC, 그리고 ANSI 등의 권고안에 기술된 국제 표준을 중심으로 요약하고 분석하였다. 분야별로는 음성 명료도, 음성 음질, 그리고 오디오 음질 평가법을 다루었으며, 현재 사용되는 권고안의 기술적인 내용과 최신 연구 동향 및 향후 발전 방향 등에 대해 기술하였다. Assessing the quality of audio signals is an important consideration in making high quality sounds and various methods have been developed. This paper provides a general framework of sound quality and a technical overview of the international standard methods which are described in ITU-T, ITU-R, IEC and ANSI Recommendations in the speech intelligibility, speech quality, and audio quality areas. In addition, some recent findings and future works are included.

Ensuring Audio Signal Quality in Automotive Infotainment Systems

Ensuring Audio Signal Quality in Automotive Infotainment Systems

Noise Cancellation and Speech Enhancement for Hearing Impaired Person

A major complaint of individuals with normal hearing and hearing impairments is a reduced ability to understand speech in a noisy environment. This paper is proposed to remove the noise from the speech signal in various real time environments and to make the hearing impaired to understand the information by transforming speech in to text format. The quality of audio signal can be improved by filtering the degraded speech signal through adaptive filters. For Noise cancellation widrow & hoff’s Least Mean Square (LMS) algorithms are being used for simplicity in implementation. The LMS algorithm was simple in it's derivation and robust in a number of applications but it also have limitation in selection of a certain values such as step size and results in computational complexity. Hence to overcome all the limitations and to present an enhanced speech signal, a novel approach named VSSNDLMS algorithm is proposed. The performance of algorithms like Variable Step Size Normalised LMS , Normalised Differential LMS with proposed VSSNDLMS with different input signals are analysed in this paper . Finally, through simulation results the proposed VSSNDLMS algorithm converges fastly with minimum mean square error and it is useful in predicting the adaptive filter performance of various algorithms and the implementation indicate the improvement in quality of the speech signal and it appears to be favourable for hearing impaired. Keywords: VSSNDLMS, LMS Algorithm, Noise Cancellation, Speech Processing, Adaptive Filter

Robust Watermarking Using Compressed Sensing Framework with Application to MP3 Audio

In this paper a watermark embedding and recovery technique is proposed based on the compressed sensing framework. Both the watermark and the host signal are sparse, each in its own domain. In recovery, the L1-minimization is used to recover the watermark and the host signal almost perfectly in clean conditions. The proposed technique is tested on MP3 audio compression-decompression attack and additive noise attack. Bit error rates are compared with standard spread spectrum embedding. The proposed technique is implemented for both time domain and frequency domain embedding with a unified approach. The WalshHadamard transform (WHT), the discrete cosine transform (DCT) and the Karhunen-Loeve transform (KLT) are compared in the host signal sparsifying process. Significant performance improvements in all tested conditions are achieved against the spread spectrum embedding. A payload as high as 172bps in additive noise attacks, 86bps in 128kbps MP3 attacks and 11bps in 64kbps MP3 attacks are achieved at small bit error rates and acceptable MP3 audio signal quality.

Real-Time Perception-Based Clipping of Audio Signals Using Convex Optimization

Clipping is an essential signal processing operation in many real-time audio applications, yet the use of existing clipping techniques generally has a detrimental effect on the perceived audio signal quality. In this paper, we present a novel multidisciplinary approach to clipping which aims to explicitly minimize the perceptible clipping-induced distortion by embedding a convex optimization criterion and a psychoacoustic model into a frame-based algorithm. The core of this perception-based clipping algorithm consists in solving a convex optimization problem for each time frame in a fast and reliable way. To this end, three different structure-exploiting optimization methods are derived in the common mathematical framework of convex optimization, and corresponding theoretical complexity bounds are provided. From comparative audio quality evaluation experiments, it is concluded that the perception-based clipping algorithm results in significantly higher objective audio quality scores than existing clipping techniques. Moreover, the algorithm is shown to be capable to adhere to real-time deadlines without making a sacrifice in terms of audio quality.