Results 11 - 20 of 56

Compressive sensing for sparsely excited speech signals

by T. V. Sreenivas, W. Bastiaan Kleijn - in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP), 2009
"... Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sens ..."
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Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived from the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra. Index Terms — sampling, compressed sensing, matching pursuit, sparse signal reconstruction 1.
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A Comparison between Fixed and Multiresolution Analysis for Onset Detection in Musical Signals

by Chris Duxbury, Juan Pablo Bello, Mark Sandler, Mark S, Mike Davies - In Proc. Digital Audio Effects Workshop (DAFx , 2004
"... A study is presented for the use of multiresolution analysis-based onset detection in the complex domain. It shows that using variable time-resolution across frequency bands generates sharper detection functions for higher bands and more accurate detection functions for lower bands. The resulting me ..."
Abstract - Cited by 9 (0 self) - Add to MetaCart
A study is presented for the use of multiresolution analysis-based onset detection in the complex domain. It shows that using variable time-resolution across frequency bands generates sharper detection functions for higher bands and more accurate detection functions for lower bands. The resulting method improves the localisation of onsets on fixed-resolution schemes, by favouring the increased time precision of higher subbands during the combination of results.
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Separation of Musical Sources and Structure from SingleChannel Polyphonic Recordings University of

by Mark Robert Every , 2006
"... The thesis deals principally with the separation of pitched sources from single-channel polyphonic musical recordings. The aim is to extract from a mixture a set of pitched instruments or sources, where each source contains a set of similarly sounding events or notes, and each note is seen as compri ..."
Abstract - Cited by 8 (0 self) - Add to MetaCart
The thesis deals principally with the separation of pitched sources from single-channel polyphonic musical recordings. The aim is to extract from a mixture a set of pitched instruments or sources, where each source contains a set of similarly sounding events or notes, and each note is seen as comprising partial, transient and noise content. The work also has implications for separating non-pitched or percussive sounds from recordings, and in general, for unsupervised clustering of a list of detected audio events in a recording into a meaningful set of source classes. The alignment of a symbolic score/MIDI representation with the recording constitutes a pre-processing stage. The three main areas of con-tribution are: firstly, the design of harmonic tracking algorithms and spectral-filtering techniques for removing harmonics from the mixture, where particular attention has been paid to the case of harmonics which are overlapping in fre-quency. Secondly, some studies will be presented for separating transient attacks from recordings, both when they are distinguishable from and when they are overlapping in time with other transients. This section also includes a method which proposes that the behaviours of the harmonic and noise components of a note are partially correlated. This is used to share the noise component of a mixture of pitched notes between the interfering sources. Thirdly, unsupervised clustering has been applied to the task of grouping a set of separated notes from the recording into sources, where notes belonging to the same source ide-ally have similar features or attributes. Issues relating to feature computation, feature selection, dimensionality and dependence on a symbolic music repre-sentation are explored. Applications of this work exist in audio spatialisation, audio restoration, music content description, effects processing and elsewhere.
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Speeding up HILN – MPEG-4 parametric audio encoding with reduced complexity

by Heiko Purnhagen, Nikolaus Meine, Bernd Edler - in AES 109th Convention , 2000
"... Parametric modelling permits an efficient representation of audio signals and is utilised for very low bit rate coding by the MPEG-4 Standard. Here we look at the MPEG-4 parametric audio coding tools ”Harmonic and Individual Lines plus Noise ” (HILN) which are based on a decomposition of the audio s ..."
Abstract - Cited by 7 (3 self) - Add to MetaCart
Parametric modelling permits an efficient representation of audio signals and is utilised for very low bit rate coding by the MPEG-4 Standard. Here we look at the MPEG-4 parametric audio coding tools ”Harmonic and Individual Lines plus Noise ” (HILN) which are based on a decomposition of the audio signal into components that are described by appropriate source models and represented by model parameters. Until now, HILN encoding mainly focused on maximum audio quality at the expense of high computational complexity. In this paper, different approaches to speed up HILN encoding are presented and the tradeoff between computational complexity and audio quality is analysed. 1
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Sinusoidal Coding Using Loudness-Based Component Selection

by Heiko Purnhagen, Nikolaus Meine, Bernd Edler - in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing , 2002
"... Sinusoidal modelling forms the base of parametric audio coding systems, like MPEG-4 HILN, where it is combined with noise and transient models. A parametric encoder decomposes the audio signal into components that are described by appropriate models and represented by model parameters. To achieve ef ..."
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Sinusoidal modelling forms the base of parametric audio coding systems, like MPEG-4 HILN, where it is combined with noise and transient models. A parametric encoder decomposes the audio signal into components that are described by appropriate models and represented by model parameters. To achieve efficient coding at very low bitrates, selection of the perceptually most relevant signal components (e.g. sinusoids) is essential, as only a limited number of component parameters can be conveyed in the bitstream. Various strategies for sinusoidal component selection have been proposed in the literature. This paper introduces a new, loudnessbased strategy and tries to compare the different strategies using objective and subjective criteria.
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MIRAI: Multi-hierarchical, FS-tree based Music Information Retrieval System

by Zbigniew W. Ra´s, Xin Zhang, Rory Lewis - Invited Paper), Proceedings of RSEISP 2007, M. Kryszkiewicz et al. (Eds), LNAI , 2007
"... Abstract. With the fast booming of online music repositories, there is a need for content-based automatic indexing which will help users to find their favorite music objects in real time. Recently, numerous successful approaches on musical data feature extraction and selection have been proposed for ..."
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Abstract. With the fast booming of online music repositories, there is a need for content-based automatic indexing which will help users to find their favorite music objects in real time. Recently, numerous successful approaches on musical data feature extraction and selection have been proposed for instrument recognition in monophonic sounds. Unfortunately, none of these methods can be successfully applied to polyphonic sounds. Identification of music instruments in polyphonic sounds is still difficult and challenging, especially when harmonic partials are overlapping with each other. This has stimulated the research on music sound separation and new features development for content-based automatic music information retrieval. Our goal is to build a cooperative query answering system (QAS), for a musical database, retrieving from it all objects satisfying queries like ”find all musical pieces in pentatonic scale with a viola and piano where viola is playing for minimum 20 seconds and piano for minimum 10 seconds”. We use the database of musical sounds, containing almost 4000 sounds taken from the MUMs (McGill University Master Samples), as a vehicle to construct several classifiers for automatic instrument recognition. Classifiers showing the best performance are adopted for automatic indexing of musical pieces by instruments. Our musical database has an FS-tree (Frame Segment Tree) structure representation. The cooperativeness of QAS is driven by several hierarchical structures used for classifying musical instruments. 1
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Transient Detection and Analysis for Diagnosis of Abrupt Faults in Continuous Dynamic Systems

by Eric-Jan Manders, Gautam Biswas
"... TRANSCEND, our system for fault detection and isolation of complex dynamic systems, uses a model based approach to predict and analyze transient effects resulting from abrupt faults in the system. Abrupt faults are attributed to discrete and persistent parameter value changes. Fault isolation is per ..."
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TRANSCEND, our system for fault detection and isolation of complex dynamic systems, uses a model based approach to predict and analyze transient effects resulting from abrupt faults in the system. Abrupt faults are attributed to discrete and persistent parameter value changes. Fault isolation is performed by matching features extracted from the transients against those predicted by the model. This paper discusses a statistical signal processing approach to transient detection and analysis using a time-frequency representation of the signal. The approach is robust for the detection task and it provides feature values for the initial fault isolation steps.

On Perceptual Distortion Minimization and Nonlinear Least-Squares Frequency Estimation

by Mads Græsbøll Christensen, Student Member, Søren Holdt Jensen, Senior Member
"... Abstract — In this paper, we present a framework for perceptual error minimization and sinusoidal frequency estimation based on a new perceptual distortion measure and we state its optimal solution. Using this framework, we relate a number of well-known practical methods for perceptual sinusoidal pa ..."
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Abstract — In this paper, we present a framework for perceptual error minimization and sinusoidal frequency estimation based on a new perceptual distortion measure and we state its optimal solution. Using this framework, we relate a number of well-known practical methods for perceptual sinusoidal parameter estimation such as the pre-filtering method, the weighted matching pursuit and the perceptual matching pursuit. In particular, we derive and compare the sinusoidal estimation criteria used in these methods. We show that for the sinusoidal estimation problem, the pre-filtering method and the weighted matching pursuit are equivalent to the perceptual matching pursuit under certain conditions. I.
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Perceptual matching pursuit for audio coding

by Hossein Najaf-zadeh, Ramin Pichevar, Hassan Lahdili, Louis Thibault - in Audio Engineering Society Convetion , 2008
"... The papers at this Convention have been selected on the basis of a submitted abstract and extended precis that have been peer reviewed by at least two qualified anonymous reviewers. This convention paper has been reproduced from the author's advance manuscript, without editing, corrections, or ..."
Abstract - Cited by 5 (4 self) - Add to MetaCart
The papers at this Convention have been selected on the basis of a submitted abstract and extended precis that have been peer reviewed by at least two qualified anonymous reviewers. This convention paper has been reproduced from the author's advance manuscript, without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for the contents.

Spectral Line Broadening with Transform Domain Additive Synthesis

by Adrian Freed , 1999
"... After a survey of inverse transform methods for the efficient synthesis of narrow-band and broad-band signals, a novel spectral line broadening technique is introduced for synthesis of pitch modulated noise signals. This new transform-domain approach is compared to the time-domain oscillator method ..."
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After a survey of inverse transform methods for the efficient synthesis of narrow-band and broad-band signals, a novel spectral line broadening technique is introduced for synthesis of pitch modulated noise signals. This new transform-domain approach is compared to the time-domain oscillator method with respect to their relative efficiency on modern processors Introduction: Noise in Musical Instrument Sounds The term "noise" is used to describe the perception of a multitude of features of sounds from musical instruments, for example: . Dense modes, e.g., cymbals . Additive "noise" from turbulence in blown instruments such as the flute or consonants in the voice. . Impulses from short-term interactions such as hammer strikes, string plucks, key and tone hole closure and openings. . Bandwidth broadening from non-linear mechanisms such as piano dampers, harpsichord quills, tampoura and the sarod jawari bridge. . Correlated or convolutional noise in blown instruments where a reed (o...