During the last decade, CD-quality digital audio has essentially replaced analog audio. Emerging digital audio applications for network, wireless, and multimedia computing systems face a series of constraints such as reduced channel bandwidth, limited storage capacity, and low cost. These new applications have created a demand for high-quality digital audio delivery at low bit rates. In response to this need, considerable research has been devoted to the development of algorithms for perceptually transparent coding of high-fidelity (CD-quality) digital audio. As a result, many algorithms have been proposed, and several have now become international and/or commercial product standards. This paper reviews algorithms for perceptually transparent coding of CD-quality digital audio, including both research and standardization activities. This paper is organized as follows. First, psychoacoustic principles are described, with the MPEG psychoacoustic signal analysis model 1 discussed in some detail. Next, filter bank design issues and algorithms are addressed, with a particular emphasis placed on the modified discrete cosine transform, a perfect reconstruction cosine-modulated filter bank that has become of central importance in perceptual audio coding. Then, we review methodologies that achieve perceptually transparent coding of FM- and CD-quality audio signals, including algorithms that manipulate transform components, subband signal decompositions, sinusoidal signal components, and linear prediction parameters, as well as hybrid algorithms that make use of more than one signal model. These discussions concentrate on architectures and applications of those techniques that utilize psychoacoustic models to exploit efficiently masking characteristics of the human receiver. Several algorithms that have become international and/or commercial standards receive in-depth treatment, including the ISO/IEC MPEG family (-1, -2, -4), the Lucent Technologies PAC/EPAC/MPAC, the Dolby AC-2/AC-3, and the Sony ATRAC/SDDS algorithms. Then, we describe subjective evaluation methodologies in some detail, including the ITU-R BS.1116 recommendation on subjective measurements of small impairments. This paper concludes with a discussion of future research directions.

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Perceptual coding of digital audio

On typical echo paths, the proportionate normalized least-mean-squares (PNLMS) adaptation algorithm converges significantly faster than the normalized least-mean-squares (NLMS) algorithm generally used in echo cancelers to date. In PNLMS adaptation, the adaptation gain at each tap position varies from position to position and is roughly proportional at each tap position to the absolute value of the current tap weight estimate. The total adaptation gain being distributed over the taps is carefully monitored and controlled so as to hold the adaptation quality (misadjustment noise) constant. PNLMS adaptation only entails a modest increase in computational complexity.

Proportionate normalized least-mean-squares adaptation in echo cancelers

We consider a sensor array located in an enclosure, where arbitrary transfer functions (TFs) relate the source signal and the sensors. The array is used for enhancing a signal contaminated by interference. Constrained minimum power adaptive beamforming, which has been suggested by Frost (1972) and, in particular, the generalized sidelobe canceler (GSC) version, which has been developed by Griffiths and Jim (1982), are the most widely used beamforming techniques. These methods rely on the assumption that the received signals are simple delayed versions of the source signal. The good interference suppression attained under this assumption is severely impaired in complicated acoustic environments, where arbitrary TFs may be encountered. In this paper, we consider the arbitrary TF case. We propose a GSC solution, which is adapted to the general TF case. We derive a suboptimal algorithm that can be implemented by estimating the TFs ratios, instead of estimating the TFs. The TF ratios are estimated by exploiting the nonstationarity characteristics of the desired signal. The algorithm is applied to the problem of speech enhancement in a reverberating room. The discussion is supported by an experimental study using speech and noise signals recorded in an actual room acoustics environment.

Signal enhancement using beamforming and nonstationarity with applications to speech

Speech separation systems usually operate on the short-time Fourier transform (STFT) of noisy speech, and enhance only the magnitude spectrum while leaving the phase spectrum unchanged. This is done because there was a belief that the phase spectrum is unimportant for speech enhancement. Recent studies, however, suggest that phase is important for perceptual quality, leading some researchers to consider magnitude and phase spectrum enhancements. We present a supervised monaural speech separation approach that simultaneously enhances the magnitude and phase spectra by operating in the complex domain. Our approach uses a deep neural network to estimate the real and imaginary components of the ideal ratio mask defined in the complex domain. We report separation results for the proposed method and compare them to related systems. The proposed approach improves over other methods when evaluated with several objective metrics, including the perceptual evaluation of speech quality (PESQ), and a listening test where subjects prefer the proposed approach with at least a 69% rate.

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Complex ratio masking for monaural speech separation

A method and an apparatus measure blood oxygenation in a subject. A first signal source applies a first input signal during a first time interval. A second signal source applies a second input signal during a second time interval. A detector detects a first parametric signal responsive to the first input signal passing through a portion of the subject having blood therein. The detector also detects a second parametric signal responsive to the second input signal passing through the portion of the subject. The detector generates a detector output signal responsive to the first and second parametric signals. A signal processor receives the detector output signal and demodulates the detector output signal by applying a first demodulation signal to a signal responsive to the detector output signal to generate a first output signal responsive to the first parametric signal. The signal processor applies a second demodulation signal to the signal responsive to the detector output signal to generate a second output signal responsive to the second parametric signal. The first demodulation signal and the second demodulation signal both include at least a first component having a first frequency and a first amplitude and a second component having a second frequency and a second amplitude. The second frequency is a harmonic of the first frequency. The second amplitude is related to the first amplitude to minimize crosstalk from the first parametric signal to the second output signal and to minimize crosstalk from the second parametric signal to the first output signal.

Method and apparatus for demodulating signals in a pulse oximetry system

This paper proposes a generalized proportionate variable step-size algorithm based on affine projection. It controls the step size for each tap individually based on the gradient approximated by the difference between the current coefficient and an averaged filter coefficient with delay. This step-size control is specifically effective for tracking fast changing acoustic environments. It is shown that the P-NLMS family and the ES algorithm are special cases of the proposed algorithm in terms of step-size control. Simulation results in the context of echo cancellation in artificial and real environments demonstrate that this step-size control combined with the affine projection algorithm (APA) reduces the echo by up to 5 dB compared to the standard APA. The best tracking performance, without a priori knowledge on the acoustic environment, among the same family of algorithms is obtained.

A generalized proportionate variable step-size algorithm for fast changing acoustic environments

A coding technique is presented for high-quality audio signals based on adaptive transform coding (ATC). Adaptive block size selection by the proposed algorithm ensures an appropriate block size resulting in improved SNR (signal-to-noise ratio) for a wide variety of source signals. A feedback approach, based on SNR, and a feedforward approach, based on interblock differences in input time-domain samples, to adaptive block size assignment are proposed and evaluated. Computer simulation results show that average segmental SNR by the feedback approach is improved by as much as 4.8 dB over the conventional fixed-block-size ATC. The feedforward approach is realized with much-simplified hardware; nevertheless, its SNR degradation from that by the feedback approach is 1.6 dB, even in the worst case. Both approaches are successful in pre-echo suppression to a satisfactory level. Time-domain aliasing cancellation has the potential to increase the superiority of the new algorithm. >

Adaptive transform coding with an adaptive block size (ATC-ABS)

This paper proposes a high speech quality noise suppression method based on weighted noise estimation and MMSE STSA. The proposed method continuously updates the noise estimate, using weighted noisy speech according to the estimated speech-to-noise ratio. In order to fully utilize the improvement offered by noise estimation, the spectral gain is corrected according to the estimated speech-to-noise ratio. By using accurate noise estimation, more accurate SNR than in the conventional method is obtained, which helps to reduce distortion in the enhanced speech. In subjective speech quality evaluations, the five-stage MOS was improved by 0.35 and 0.40 at the maximum, respectively, for the cases in which the speech was encoded and was not encoded after noise suppression. The improved version, which was developed on the basis of the proposed noise suppressor, satisfies all 3GPP minimum requirements for speech quality and has been installed in a commercially available model. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(2): 43–53, 2006; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/ecjc.20145

Noise suppression with high speech quality based on weighted noise estimation and MMSE STSA

A noise suppression algorithm with high speech quality based on weighted noise estimation and MMSE STSA is proposed. The proposed algorithm continuously updates the noise estimate by noisy speech weighted in accordance with an estimated SNR. The spectral gain is modified with the estimated SNR so that it can better utilize the improvement in noise estimation. Subjective evaluation results show that five-grade mean opinion scores of the new algorithm are improved by as much as 0.93 and 0.35, compared with the original MMSE STSA and the EVRC noise suppression algorithm, respectively.

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Noise Suppression with High Speech Quality Based on Weighted Noise Estimation and MMSE STSA

A Hi-Fi audio codec with an improved adaptive transform coding (ATC) algorithm is presented using digital signal processors (DSPs). An audio signal with a 20 kHz bandwidth sampled at 48 kHz is coded at a rate of 128 kb/s. The algorithm utilizes adaptive block size selection, which is effective for preecho suppression. A modified discrete cosine transform (MDCT) with a simple window set is employed to reduce block boundary noise without decreasing the performance of transform coding. In addition, a fast MDCT calculation algorithm, based on a fast Fourier transform, is adopted. Weighted bit allocation is employed to quantize the transformed coefficients. The codec was realized by a multiprocessor system composed of newly developed DSP boards. Subjective tests with the codec show that the coding quality is comparable to that of compact disc signals. >

Akihiko Sugiyama

Papers

A generalized proportionate variable step-size algorithm for fast changing acoustic environments

Adaptive transform coding with an adaptive block size (ATC-ABS)

Noise suppression with high speech quality based on weighted noise estimation and MMSE STSA

Noise Suppression with High Speech Quality Based on Weighted Noise Estimation and MMSE STSA

A 128 Kb/s Hi-Fi audio codec based on adaptive transform coding with adaptive block size MDCT