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Perceptual models exploiting auditory masking are frequently used in audio and speech processing applications like coding and watermarking. In most cases, these models only take into account spectral masking in short-time frames. As a consequence, undesired audible artifacts in the temporal domain may be introduced (e.g., pre-echoes). In this article we present a new low-complexity spectro-temporal distortion measure. The model facilitates the computation of analytic expressions for masking thresholds, while advanced spectro-temporal models typically need computationally demanding adaptive procedures to find an estimate of these masking thresholds. We show that the proposed method gives similar masking predictions as an advanced spectro-temporal model with only a fraction of its computational power. The proposed method is also compared with a spectral-only model by means of a listening test. From this test it can be concluded that for non-stationary frames the spectral model underestimates the audibility of introduced errors and therefore overestimates the masking curve. As a consequence, the system of interest incorrectly assumes that errors are masked in a particular frame, which leads to audible artifacts. This is not the case with the proposed method which correctly detects the errors made in the temporal structure of the signal., QC 20120504

Modern networks are highly variable and, as a result, source coders are commonly used under conditions that they were not designed for. We address this problem with a source-coding philosophy that aims at the instantaneous re-optimization of a source coder to match a wide range of constraints on rate or quality and a wide range of packet-loss rates. We present a number of technologies that can be reconfigured by solving analytic relations that use the current conditions and a statistical description of the source as input. The technologies include distribution-preserving quantizers, flexible multiple-description quantizers, and a rate distribution scheme. Based on the generic technologies, we created a complete audio coder. Formal listening tests show that the resulting audio coding scheme with full flexibility provides a quality that is on-par with the best standardized codecs for any particular rate., QC 20110418

An FPGA-based approach is proposed for implementing a compression system developed specifically for the signal of phonocardiogram. The compression method offers better rate and distorsion than standard audio compression techniques. Both the algorithm and the details on the solutions adopted for its implementation are presented in this paper., This work has been supported by Ministerio de Ciencia y Tecnología of Spain, under grant TIN2006-15460-C04-04.

We consider the rate allocation problem for multiple-description quantization of the signal described by an adaptive model with a fixed structure. The source modeling in coding generally results in a two-stage description of the data, where one of the stages describes the model parameters, and the other describes the signal. Such a setup implies the existence of a trade-off between the rate spent on the parameters and the rate spent on the signal. We optimize this trade-off analytically for the multiple-description case using a method inspired by Minimum Description Length principle. We also provide an algorithm for optimizing the rate allocation between the components of the model-based multiple description coder. Finally we experimentally confirm our results. Our method facilitates the rate-adaptive multiple-description coding., QC 20110309

The use of psychoacoustical masking models for audio coding applications has been wide spread over the past decades. In such applications, it is typically assumed that the original input signal serves as a masker for the distortions that are introduced by the lossy coding method that is used. Up to now, these masking models are mostly based on spectral masking. In this paper, we propose a new perceptual model for audio and speech processing algorithms based on spectro-temporal masking. A sophisticated perceptual model is simplified, such that the eventual distortion measure can be written as a frequency-weighted l2-norm. This yields the same computational complexity as conventional spectral-based methods, but with the preservation of the temporal fine structure of the clean signal. It is shown that the new model can successfully avoid pre-echoes and can correctly predict masking curves for various maskers., QC 20120808

An FPGA-based approach is proposed for implementing a compression system developed specifically for the signal of phonocardiogram. The compression method offers better rate and distorsion than standard audio compression techniques. Both the algorithm and the details on the solutions adopted for its implementation are presented in this paper.

We consider streaming pre-encoded and packetized media over best-effort networks in the presence of acknowledgment feedbacks. We first review a rate-distortion (RD) optimization framework that can be employed in such scenarios. As part of the framework, a scheduling algorithm selects the data to send over the network at any given time, so as to minimize the end-to-end distortion, given an estimate of channel resources and a history of previous transmissions and received acknowledgements. In practice, a greedy scheduling strategy is often considered to limit the solution search space, and reduce the computational complexity associated to the RD optimization framework. Our work observes that popular greedy schedulers are strongly penalized by early retransmissions. Therefore, we propose a scheduling algorithm that avoids premature retransmissions, while preserving the low computational complexity aspect of the greedy paradigm. Such a scheduling strategy maintains close to optimal RD performance when adapting to network bandwidth fluctuations. Our experimental results demonstrate that the proposed patient greedy scheduler provides a reduction of up to 50% in transmission rate relative to conventional greedy approaches, and that it brings up to 2 dB of quality improvement in scheduling classical MPEG-based packet video streams.

Résumé : Afin de répondre aux besoins de communication et de divertissement, il ne fait aucun doute que la parole et l’audio doivent être encodés sous forme numérique. En qualité CD, cela nécessite un débit numérique de 1411.2 kb/s pour un signal stéréo-phonique. Une telle quantité de données devient rapidement prohibitive pour le stockage de longues durées d’audio ou pour la transmission sur certains réseaux, particulièrement en temps réel (d’où l’adhésion universelle au format MP3). De plus, ces dernières années, la quantité de productions musicales et cinématographiques disponibles en cinq canaux et plus ne cesse d’augmenter. Afin de maintenir le débit numérique à un niveau acceptable pour une application donnée, il est donc naturel pour un codeur audio à bas débit d’exploiter la redondance entre les canaux et la psychoacoustique binaurale. Le codage perceptuel et plus particulièrement le codage paramétrique permet d’atteindre des débits manifestement inférieurs en exploitant les limites de l’audition humaine (étudiées en psychoacoustique). Cette recherche se concentre donc sur le codage paramétrique à bas débit de plus d’un canal audio. // Abstract : In order to fulfill our communications and entertainment needs, there is no doubt that speech and audio must be encoded in digital format. In"CD" quality, this requires a bit-rate of 1411.2 kb/s for a stereo signal. Such a large amount of data quickly becomes prohibitive for long-term storage of audio or for transmitting on some networks, especially in real-time (leading to a universal adhesion to the MP3 format). Moreover, throughout the course of these last years, the number of musical and cinematographic productions available in five channels or more continually increased.In order to maintain an acceptable bit-rate for any given application, it is obvious that a low bit-rate audio coder must exploit the redundancies between audio channels and binaural psychoacoustics. Perceptual audio coding, and more specificall

In this work, we develop a new method for quantization in multistage audio coding. Given a (perceptual) distortion measure and a bit-rate constraint, we analytically derive the optimal rate distribution between subcoders (stages) and the corresponding optimal quantizers using high-rate theory. The analytical solutions for optimal quantizers allow a coder to easily adapt to changes in bit-rate requirements. As an illustration of the new method, we consider quantization in a two-stage sinusoidal/wave form coder that is a widely used combination in audio coding. We show that at low total rates most of the rate should be assigned to the sinusoidal (model-based, subspace) subcoder, while at high total rates most of the rate should be assigned to the waveform (full-space) subcoder. We compare the new method to a reference quantization method that does not use rate-distortion optimization. A significantly higher performance of the new method is shown by means of a listening test., QC 20100525

not available, Electrical Engineering, Mathematics and Computer Science

With the arrival of new hardware and software technologies, supervisory control and data acquisition human-machine interfaces (SCADA/HMI), usually text-based, can now benefit from the advantages the inclusion of multimedia information brings. However, due to the special requirements imposed by such systems, integrating audio and video data into the SCADA interfaces is not a trivial task. In this document we analyze those special characteristics and propose solutions so this integration is possible in power systems communication.

We introduce multivariate block polar quantization (MBPQ). MBPQ minimizes the weighted squared-error distortion for a set of complex variables representing one block of a signal under a resolution constraint for the entire block. MBPQ performs below the lower bound for classical bivariate quantization, both for Gaussian complex variables and for complex variables found from sinusoidal analysis of audio data. Still, it is of similar complexity as traditional polar quantizers. In the case of audio data, we found a performance gain of about 2.5 dB over the best performing conventional resolution-constrained polar quantization (an extension of unrestricted polar quantization)., QC 20100525 QC 20111012

In this work, we develop a new method for jointly optimal quantization of sinusoidal frequencies, amplitudes, and phases and apply the method to sinusoidal audio coding. This is an extension of an earlier work on quantization of sinusoidal amplitudes and phases to frequencies. The optimization is performed for a set of sinusoids that models a short segment of an audio signal. For a given bit-rate constraint, the optimal quantizers minimize a single-letter weighted distortion measure that accounts for perceptual importance of sinusoids. The quantizers are derived analytically using high-rate theory. The method yields high performance and has a number of practical advantages over conventional sinusoidal quantization methods., QC 20100525

In, this work, we present a new method for quantization of sinusoidal amplitudes and phases, and apply the method to sinusoldal coding of speech and audio signals. The method is based on unrestricted polar quantization, where phase quantization accuracy depends on amplitude. Amplitude and phase quantizers are derived under an entropy (average rate) constraint using high-rate assumptions. First, we derive optimal quantizers for one sinusoid and a mean-squared error distortion measure. We provide a detailed analysis of entropy-constrained unrestricted polar quantization, showing its high performance and practicality even at low rates. Second, we find optimal quantizers for a set of sinusoids that model a short segment of an audio signal. The optimization is performed using a, weighted error measure that can account for the masking effect in the human auditory system. We find the optimal rate distribution between, sinusoids, as well as the corresponding optimal amplitude and phase quantizers, based on the perceptual importance of sinusolds defined by masking. The new method is used in an audio-coding application and is shown to significantly outperform a conventional sinsoidal quantization method where phase quantization accuracy is identical for all sinusoids., QC 20100525

Sinusoidal coding plays an important role in low-rate audio coding. Typically, (time/frequency) differential techniques are employed to reduce the bit rate for representing the sinusoidal components. In this paper we derive optimal entropy-constrained differential quantisers for quantising the sinusoid parameters. More specifically, the quantisers minimise a perceptually relevant distortion measure while the corresponding quantisation indices satisfy an entropy constraint. The quantisers turn out to be flexible and of low complexity. Subjective evaluations with audio signals suggest a bit-rate reduction as high as 20% with the derived quantisers over state-of-the-art (logarithmic) quantisers., QC 20141217

The purpose of this thesis work done at Ericsson Research in Luleå was to investigate the possibilities of encoding 5.1 surround sound for low bit rates using the AMR-WB+ audio encoding technique. In the first phase of the work, investigations of the inter-channel dependencies were carried out, and the main tool used was Matlab. Several efforts were made aiming to reduce the total energy of the signal. This was done by decorrelating the sound channels using ordinary linear predictors. Decorrelation attempts were performed in the time domain as well as in the frequency domain. After decorrelating the channels, each channel was encoded in an individual bit rate using the mono mode of AMR-WB+ with bit rates proportional to the relative energy content. However, listening tests combined with studies of the energy reduction achieved by decorrelations indicated that, for a given bit rate, there is in general no advantage decorrelating the signal compared to not doing so. The second phase of the thesis work mainly consisted of modifying the existent C code of the AMR-WB+ mono coder in order to suit it for 5.1 sound encoding and decoding. The goal was "the simplest possible", an encoder that encoded each unmodified sound channel individually, distributing the bit rates over the channels aiming to keep the sums of the bit rates over the channels approximately constant over time. Opposed to the five "normal" sound channels, the encoding of the LFE (Low Frequency Element) was done in a specific way making use of this, compared to the other channels, somewhat constrained signal. Furthermore, the method of encoding high frequency sounds of AMR-WB+, the BWE (BandWidth Extension), needed to be modified at some extent. Finally, the third phase consisted mainly of evaluation of the product made and of making comparisons to competing low bit rate multi channel coders., Validerat; 20101217 (root)

Psychoacoustical models have been used extensively within audio coding applications over the past decades. Recently, parametric coding techniques have been applied to general audio and this has created the need for a psychoacoustical model that is specifically suited for sinusoidal modelling of audio signals. In this paper, we present a new perceptual model that predicts masked thresholds for sinusoidal distortions. The model relies on signal detection theory and incorporates more recent insights about spectral and temporal integration in auditory masking. As a consequence, the model is able to predict the distortion detectability. In fact, the distortion detectability defines a (perceptually relevant) norm on the underlying signal space which is beneficial for optimisation algorithms such as rate-distortion optimisation or linear predictive coding. We evaluate the merits of the model by combining it with a sinusoidal extraction method and compare the results with those obtained with the ISO MPEG-1 Layer I-II recommended model. Listening tests show a clear preference for the new model. More specifically, the model presented here leads to a reduction of more than 20% in terms of number of sinusoids needed to represent signals at a given quality level., Mediamatics, Electrical Engineering, Mathematics and Computer Science

thesis is about audio coding and improving flexibility thereof. Audio coding is used to reduce the bit rate needed to represent audio signals in digital format. When the available bit rate is low, parametric coding methods that use models to describe perceptually-important features of audio signals have shown their efficiency. We introduce several improvements to sinusoidal coding, a parametric coding method that is based on sinusoidal modeling of audio. Flexibility is important since new applications bring a need for coders that can operate over a large range of possible bit rates and are able to represent different types of audio material. Flexibility can be obtained by combining into one coder a set of subcoders that can efficiently represent different types or features of audio signals, and properly complement each other at different rates. For true flexibility, methods that allow fast coder adaptation should be deployed. We develop methods for rate-distortion optimal real-time design of quantizers in audio coding. This thesis consists of seven research papers. In paper A, we introduce a signal pre-processing method that facilitates removal of pre-echo artifacts when coding signals containing transients (sharp attacks). Papers B-F are devoted to sinusoidal audio coding. In papers B and C, we present improvements to the matching-pursuit sinusoidal estimation method. In papers D, E, and F, we consider quantization of sinusoidal parameters. We apply high-rate quantization theory to find the asymptotically optimal rate distribution between sinusoids and the corresponding asymptotically optimal quantizers for sinusoidal parameters, such that a perceptual distortion measure is minimized under a given rate constraint. The quantizers are derived analytically, which allows a coder to adapt quickly to changing bit-rate requirements. Paper G is devoted to multistage audio coding, a coding method where subcoders are combined in a cascaded way. We use high-rate theory to dev

In the process of quantization, speech and audio signals are changed. This thesis contains four papers concerned with comparing and minimizing different measures to quantify the changes introduced. Before quantization the signal can be transformed to another domain. Transforms related to the discrete Fourier transform allow for e.cient quantization. The complex coe.cients from these transforms are typically represented by their amplitudes and phases. Papers A and B describe a new method to quantize the amplitudes and phases with scalar polar quantizers. The method is denoted as multi-variate block polar quantization (MBPQ) and is optimized to minimize the average weighted squared error, utilizing high-rate derivations. It is shown that MBPQ outperforms other polar quantizers for all types of data considered. While the perceptual importance of the amplitude values is well established, the perceptual importance of the phase values is still discussed. In paper C, two distortion measures quantifying the detectability of phase distortions are found and veri.ed. Utilizing these distortion measures, it is investigated how well the squared error describes the perception of phase distortions. It was found that the average perceptual distortion reduces only moderately with increasing rate for both vector quantizers minimizing a weighted squared error and vector quantizers minimizing a perceptual distortion measure. It is concluded that future research should focus on .nding parameters that describe the features contained in phase and lead to more e.cient quantization. Paper D investigates perceptual distortion measures in the most commonly used coder paradigm for speech coding: linear-prediction-based analysis-by-synthesis. In the paper, an auditory model based distortion measure is compared to a commonly used weighted squared error derived from the linear prediction coe.cients. It is concluded that sophisticated auditory models are rarely used in this type of coders due to t

Ogg Vorbis is a rather new audio format with some similarities with other more known formats such as MP3 and WMA. It is generally accepted to have a better audio quality than most competing formats and it is in contrast to many of its competitors totally licence and royalty free. The goal with this thesis is to port the existing fixed point decoder Tremor, which is written in C, to Motorola's DSP56002. The DSP has a very limited amount of memory so some optimizations has to be made to be able to run Tremor successfully. The report presents the necessary steps taken to port Tremor to the DSP and the difficulties of this process. It also describes the memory and CPU usage of the DSP when running Tremor and other results of the port. A description as well as examples and workarounds of bugs found in the compiler g56k is attached to this report.

Digital audio is increasingly becoming more and more a part of our daily lives. Unfortunately, the excessive bitrate associated with the raw digital signal makes it an extremely expensive representation. Applications such as digital audio broadcasting, high definition television, and internet audio, require high quality audio at low bitrates. The field of audio coding addresses this important issue of reducing the bitrate of digital audio, while maintaining a high perceptual quality. Developing an efficient audio coder requires a detailed analysis of the audio signals themselves. It is important to find a representation that can concisely model any general audio signal. In this thesis, we propose two new high quality audio coders based on two different audio representations - the sinusoidal-wavelet representation, and the warped linear predictive coding (WLPC)-wavelet representation. In addition to high quality coding, it is also important for audio coders to be flexible in their application. With the increasing popularity of internet audio, it is advantageous for audio coders to address issues related to real-time audio delivery. The issue of bitstream scalability has been targeted in this thesis, and therefore, a third audio coder capable of bitstream scalability is also proposed. The performance of each of the proposed coders was evaluated by comparisons with the MPEG layer III coder. The first coder proposed is based on a hybrid sinusoidal-wavelet representation. This assumes that each frame of audio can be modelled as a sum of sinusoids plus a noisy residual. The discrete wavelet transform (DWT) is used to decompose the residual into subbands that approximate the critical bands of human hearing. A perceptually derived bit allocation algorithm is then used to minimise the audible distortions introduced from quantising the DWT coefficients. Listening tests showed that the coder delivers near-transparent quality for a range of critical audio signals at G4 kbps. It

This paper proposes a technique for scalable and also provides for lossless compression. It reduces smooth objective scalability, in terms of SegSNR, from lossy to lossless compression. The proposal is built around the perceptual SPIHT algorithm, which is a modification of the SPIHT algorithm and is introduced in this paper. Both objective and subjective results are reported and demonstrate that the proposed method performs comparably with the MPEG-4 AAC coder at 16, 32 and 64 kbps, yet also achieves a scalable-to-lossless architecture.

This paper presents a scalable to lossless compression scheme that allows scalability in terms of sampling rate as well as quantization resolution. The scheme presented is perceptually scalable and it also allows lossless compression. The scheme produces smooth objective scalability, in terms of SNR, until lossless compression is achieved. The scheme is built around the perceptual SPIHT algorithm, which is a modification of the SPIHT algorithm. Objective and subjective results are given that show perceptual as well as objective scalability. The subjective results given also show that the proposed scheme performs comparably with the MPEG-4 AAC coder at 16, 32 and 64 kbps.

This paper describes the use of sorted sinusoidal parameters to produce a fixed rate, scalable, wideband audio coder. The sorting technique relies on the perceptual significance of the sinusoidal parameters. Sinusoidal coding permits the representation of a given signal through the summation of sinusoids. The parameters of the sinusoids (the amplitudes, phases and frequencies) are transmitted to allow signal reconstruction. The sinusoidal parameters are sorted according to energy content and perceptual significance. The most significant parameters are transmitted first, allowing the use of only a small set of the parameters for signal reconstruction. The proposed scheme incurs a low delay and uses a 20 ms frame length. The results presented show the advantages gained for scalable audio coding by sorting the parameters.

This paper describes a new audio coding scheme based on sinusoidal coding of signals. Sinusoidal coding permits the representation of a given signal through the summation of sinusoids. The parameters of the sinusoids (the amplitudes, phases and frequencies) are transmitted to allow the signal reconstruction. In the proposed scheme, the sinusoidal parameters are sorted according to energy content and perceptual significance. The most significant parameters are transmitted first allowing the use of only a small set of the parameters for signal reconstruction. The proposed scheme incurs a low delay and uses a 20 ms frame length. Results show that the coder operating at a mean rate of 39 kb/s, performs favorably in comparison with the MPEG-4 coder at 42 kb/s.

This paper describes the preliminary work in the development of an MPEG-4 audio transcoder between the time/frequency (T/F) and the structured audio (SA) formats. Our approach consists in not going from T/F format through to waveform data and back again to SA, but extracting the score information from an intermediate stage. For this intermediate form we have chosen the input of the filterbank and block switching tool, which consists of frequency data. This data is the result of windowing and applying the modified discrete cosine transform (MDCT) to the signal. The size of the window to be used is determined in a frame-by-frame basis by a psychoacoustics analysis of the data. In this paper we show that this approach is feasible by developing a system which extracts the score information from the filterbank and block switching tool output in a MPEG-4 T/F encoder by adapting and fine-tuning some existing processing techniques., Peer Reviewed, Postprint (published version)