Acoustic Signature

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Avshalom Manela - One of the best experts on this subject based on the ideXlab platform.

  • On the Acoustic Signature of tandem airfoils: The sound of an elastic airfoil in the wake of a vortex generator
    Physics of Fluids, 2016
    Co-Authors: Avshalom Manela
    Abstract:

    The Acoustic Signature of an Acoustically compact tandem airfoil setup in uniform high-Reynolds number flow is investigated. The upstream airfoil is considered rigid and is actuated at its leading edge with small-amplitude harmonic pitching motion. The downstream airfoil is taken passive and elastic, with its motion forced by the vortex-street excitation of the upstream airfoil. The non-linear near-field description is obtained via potential thin-airfoil theory. It is then applied as a source term into the Powell-Howe Acoustic analogy to yield the far-field dipole radiation of the system. To assess the effect of downstream-airfoil elasticity, results are compared with counterpart calculations for a non-elastic setup, where the downstream airfoil is rigid and stationary. Depending on the separation distance between airfoils, airfoil-motion and airfoil-wake dynamics shift between in-phase (synchronized) and counter-phase behaviors. Consequently, downstream airfoil elasticity may act to amplify or suppress s...

  • on the Acoustic Signature of tandem airfoils the sound of an elastic airfoil in the wake of a vortex generator
    Physics of Fluids, 2016
    Co-Authors: Avshalom Manela
    Abstract:

    The Acoustic Signature of an Acoustically compact tandem airfoil setup in uniform high-Reynolds number flow is investigated. The upstream airfoil is considered rigid and is actuated at its leading edge with small-amplitude harmonic pitching motion. The downstream airfoil is taken passive and elastic, with its motion forced by the vortex-street excitation of the upstream airfoil. The non-linear near-field description is obtained via potential thin-airfoil theory. It is then applied as a source term into the Powell-Howe Acoustic analogy to yield the far-field dipole radiation of the system. To assess the effect of downstream-airfoil elasticity, results are compared with counterpart calculations for a non-elastic setup, where the downstream airfoil is rigid and stationary. Depending on the separation distance between airfoils, airfoil-motion and airfoil-wake dynamics shift between in-phase (synchronized) and counter-phase behaviors. Consequently, downstream airfoil elasticity may act to amplify or suppress sound through the direct contribution of elastic-airfoil motion to the total signal. Resonance-type motion of the elastic airfoil is found when the upstream airfoil is actuated at the least stable eigenfrequency of the downstream structure. This, again, results in system sound amplification or suppression, depending on the separation distance between airfoils. With increasing actuation frequency, the Acoustic signal becomes dominated by the direct contribution of the upstream airfoil motion, whereas the relative contribution of the elastic airfoil to the total Signature turns negligible.

Clémentine Vignal - One of the best experts on this subject based on the ideXlab platform.

  • Vocal behaviour of mates at the nest in the White-throated Dipper Cinclus cinclus: contexts and structure of vocal interactions, pair-specific Acoustic Signature
    Journal of Ornithology, 2017
    Co-Authors: Avelyne S. Villain, Mathieu Mahamoud-issa, Blandine Doligez, Clémentine Vignal
    Abstract:

    Birdsong has been extensively studied in the context of sexual selection, and intersexual vocal communication prior to pair formation has been the focus of most interest. With the exception of conspicuous vocal duets of tropical bird species, descriptions of intra-pair vocal communication are missing for most other bird species. This communication can take different forms, fulfil different functions and be more widespread than previously described. Females and males of the White-throated Dipper Cinclus cinclus, a European bird species, have been reported to sing during pair formation, but vocal communication between mates after this phase has not been investigated to date. We report here our study of the vocal behaviour between mates at the nest and describe the specific contexts and structure of the various vocal interactions both during incubation and while brooding hatchlings (N = 23 pairs). Vocal interactions were mainly composed of two vocalization types: ‘trills’ and ‘notes’, with trills being more common at the beginning of the vocal sequence. Both the Acoustic features of the vocalizations and the temporal organization of the vocal sequences changed between the two breeding stages. In particular, compared to the trills and notes produced during the incubation period, those produced while brooding were lower in pitch, and female–male vocal sequences were composed of more notes and songs, with a lower overlap rate. This difference may reflect changes in parental activities. Trills and notes carried a pair-specific Acoustic Signature. This first description of Acoustic communication between mates during breeding in the White-throated Dipper lays the basis for future investigation of the functions of the different vocalizations.ZusammenfassungDas Stimmverhalten der Brutpartner am Nest bei WasseramselnCinclus cinclus: Kontext und Struktur stimmlicher Interaktionen und paarspezifische akustische Signaturen Im Kontext sexueller Selektion wurde der Vogelgesang bereits ausführlich untersucht; dabei wurde der stimmlichen Kommunikation zwischen den Geschlechtern im Vorfeld der Paarbildung die meiste Aufmerksamkeit zuteil. Mit Ausnahme der auffälligen Duette tropischer Arten fehlen aber für die meisten Taxa immer noch Beschreibungen der stimmlichen Kommunikation zwischen den Partnern, welche unterschiedliche Formen annehmen, verschiedene Funktionen erfüllen und weiter verbreitet sein könnten als bisher beschrieben. In dieser Arbeit beschreiben wir das Stimmverhalten der Brutpartner am Nest bei Wasseramseln Cinclus cinclus, einer europäischen Vogelart, bei der Weibchen und Männchen während der Paarbildung singen, deren Kommunikation zwischen den Partnern nach dieser Phase jedoch noch nie untersucht wurde. Wir schildern Kontext und Struktur der stimmlichen Interaktionen zwischen den Brutpartnern am Nest während der Bebrütung des Geleges und des Huderns der Nestlinge (N = 23 Paare). Die stimmlichen Interaktionen bestanden hauptsächlich aus zwei Lautäußerungstypen: „Trillern“ und „Tönen“, wobei Triller am Anfang der Stimmfolgen häufiger waren. Sowohl die akustischen Merkmale der Lautäußerungen als auch die zeitliche Organisation der Ruffolgen veränderten sich über die Phasen des Brutgeschehens. Im Speziellen hatten Triller und Töne während des Huderns tiefere Tonlagen und die Lautäußerungssequenzen von Weibchen und Männchen bestanden aus mehr Tönen sowie Gesängen und hatten eine niedrigere Überlappungsrate. Dies könnte Veränderungen in den elterlichen Aktivitäten widerspiegeln. Triller und Töne wiesen eine paarspezifische akustische Signatur auf. Diese erste Beschreibung der akustischen Kommunikation zwischen den Wasseramsel-Partnern während der Brutzeit legt den nötigen Grundstein für die Untersuchung ihrer Funktionen.

  • Vocal behaviour of mates at the nest in the White-throated Dipper Cinclus cinclus: contexts and structure of vocal interactions, pair-specific Acoustic Signature
    Journal of Ornithology, 2017
    Co-Authors: Avelyne S. Villain, Mathieu Mahamoud-issa, Blandine Doligez, Clémentine Vignal
    Abstract:

    Birdsong has been extensively studied in the context of sexual selection, and intersexual vocal communication prior to pair formation has been the focus of most interest. With the exception of conspicuous vocal duets of tropical bird species, descriptions of intra-pair vocal communication are missing for most other bird species. This communication can take different forms, fulfil different functions and be more widespread than previously described. Females and males of the White-throated Dipper Cinclus cinclus , a European bird species, have been reported to sing during pair formation, but vocal communication between mates after this phase has not been investigated to date. We report here our study of the vocal behaviour between mates at the nest and describe the specific contexts and structure of the various vocal interactions both during incubation and while brooding hatchlings ( N  = 23 pairs). Vocal interactions were mainly composed of two vocalization types: ‘trills’ and ‘notes’, with trills being more common at the beginning of the vocal sequence. Both the Acoustic features of the vocalizations and the temporal organization of the vocal sequences changed between the two breeding stages. In particular, compared to the trills and notes produced during the incubation period, those produced while brooding were lower in pitch, and female–male vocal sequences were composed of more notes and songs, with a lower overlap rate. This difference may reflect changes in parental activities. Trills and notes carried a pair-specific Acoustic Signature. This first description of Acoustic communication between mates during breeding in the White-throated Dipper lays the basis for future investigation of the functions of the different vocalizations. Das Stimmverhalten der Brutpartner am Nest bei Wasseramseln Cinclus cinclus : Kontext und Struktur stimmlicher Interaktionen und paarspezifische akustische Signaturen Im Kontext sexueller Selektion wurde der Vogelgesang bereits ausführlich untersucht; dabei wurde der stimmlichen Kommunikation zwischen den Geschlechtern im Vorfeld der Paarbildung die meiste Aufmerksamkeit zuteil. Mit Ausnahme der auffälligen Duette tropischer Arten fehlen aber für die meisten Taxa immer noch Beschreibungen der stimmlichen Kommunikation zwischen den Partnern, welche unterschiedliche Formen annehmen, verschiedene Funktionen erfüllen und weiter verbreitet sein könnten als bisher beschrieben. In dieser Arbeit beschreiben wir das Stimmverhalten der Brutpartner am Nest bei Wasseramseln Cinclus cinclus , einer europäischen Vogelart, bei der Weibchen und Männchen während der Paarbildung singen, deren Kommunikation zwischen den Partnern nach dieser Phase jedoch noch nie untersucht wurde. Wir schildern Kontext und Struktur der stimmlichen Interaktionen zwischen den Brutpartnern am Nest während der Bebrütung des Geleges und des Huderns der Nestlinge (N = 23 Paare). Die stimmlichen Interaktionen bestanden hauptsächlich aus zwei Lautäußerungstypen: „Trillern“ und „Tönen“, wobei Triller am Anfang der Stimmfolgen häufiger waren. Sowohl die akustischen Merkmale der Lautäußerungen als auch die zeitliche Organisation der Ruffolgen veränderten sich über die Phasen des Brutgeschehens. Im Speziellen hatten Triller und Töne während des Huderns tiefere Tonlagen und die Lautäußerungssequenzen von Weibchen und Männchen bestanden aus mehr Tönen sowie Gesängen und hatten eine niedrigere Überlappungsrate. Dies könnte Veränderungen in den elterlichen Aktivitäten widerspiegeln. Triller und Töne wiesen eine paarspezifische akustische Signatur auf. Diese erste Beschreibung der akustischen Kommunikation zwischen den Wasseramsel-Partnern während der Brutzeit legt den nötigen Grundstein für die Untersuchung ihrer Funktionen.

  • vocal behaviour of mates at the nest in the white throated dipper cinclus cinclus contexts and structure of vocal interactions pair specific Acoustic Signature
    Journal of Ornithology, 2017
    Co-Authors: Avelyne S. Villain, Blandine Doligez, Mathieu Mahamoudissa, Clémentine Vignal
    Abstract:

    Birdsong has been extensively studied in the context of sexual selection, and intersexual vocal communication prior to pair formation has been the focus of most interest. With the exception of conspicuous vocal duets of tropical bird species, descriptions of intra-pair vocal communication are missing for most other bird species. This communication can take different forms, fulfil different functions and be more widespread than previously described. Females and males of the White-throated Dipper Cinclus cinclus, a European bird species, have been reported to sing during pair formation, but vocal communication between mates after this phase has not been investigated to date. We report here our study of the vocal behaviour between mates at the nest and describe the specific contexts and structure of the various vocal interactions both during incubation and while brooding hatchlings (N = 23 pairs). Vocal interactions were mainly composed of two vocalization types: ‘trills’ and ‘notes’, with trills being more common at the beginning of the vocal sequence. Both the Acoustic features of the vocalizations and the temporal organization of the vocal sequences changed between the two breeding stages. In particular, compared to the trills and notes produced during the incubation period, those produced while brooding were lower in pitch, and female–male vocal sequences were composed of more notes and songs, with a lower overlap rate. This difference may reflect changes in parental activities. Trills and notes carried a pair-specific Acoustic Signature. This first description of Acoustic communication between mates during breeding in the White-throated Dipper lays the basis for future investigation of the functions of the different vocalizations.

Mario E Munich - One of the best experts on this subject based on the ideXlab platform.

  • bayesian subspace methods for Acoustic Signature recognition of vehicles
    European Signal Processing Conference, 2004
    Co-Authors: Mario E Munich
    Abstract:

    Vehicles may be recognized from the sound they make when moving, i.e., from their Acoustic Signature. Characteristic patterns may be extracted from the Fourier description of the Signature and used for recognition. This paper compares conventional methods used for speaker recognition, namely, systems based on Mel-frequency cepstral coefficients (MFCC) and either Gaussian mixture models (GMM) or hidden Markov models (HMM), with Bayesian subspace method based on the short term Fourier transform (STFT) of the vehicles' Acoustic Signature. A probabilistic subspace classifier achieves a 11.7% error for the ACIDS database, outperforming conventional MFCC-GMM- and MFCC-HMM-based systems by 50%.

  • EUSIPCO - Bayesian subspace methods for Acoustic Signature recognition of vehicles
    2004
    Co-Authors: Mario E Munich
    Abstract:

    Vehicles may be recognized from the sound they make when moving, i.e., from their Acoustic Signature. Characteristic patterns may be extracted from the Fourier description of the Signature and used for recognition. This paper compares conventional methods used for speaker recognition, namely, systems based on Mel-frequency cepstral coefficients (MFCC) and either Gaussian mixture models (GMM) or hidden Markov models (HMM), with Bayesian subspace method based on the short term Fourier transform (STFT) of the vehicles' Acoustic Signature. A probabilistic subspace classifier achieves a 11.7% error for the ACIDS database, outperforming conventional MFCC-GMM- and MFCC-HMM-based systems by 50%.

Howard R Kirby - One of the best experts on this subject based on the ideXlab platform.

  • Vehicle classification by Acoustic Signature
    Mathematical and Computer Modelling, 1998
    Co-Authors: Amir Y Nooralahiyan, Howard R Kirby, Denis Mckeown
    Abstract:

    The aim of this research is to investigate the feasibility of developing a traffic monitoring detector for the purpose of reliable on-line vehicle classification to aid traffic management systems. The detector used was a directional microphone connected to a DAT (Digital Audio Tape) recorder. The digital signal was preprocessed by LPC (Linear Predictive Coding) parameter conversion based on autocorrelation analysis. A Time Delay Neural Network (TDNN) was chosen to classify individual travelling vehicles based on their speed-independent Acoustic Signature. The paper provides a description of the TDNN architecture and training algorithm, and an overview of the LPC preprocessing and feature extraction technique as applied to audio monitoring of road traffic. The performance of TDNN vehicle classification, convergence, and accuracy for the training patterns are fully illustrated. To establish the viability of this classification approach, initially, recordings were carried out on a strip of airfield for four types of vehicles under controlled conditions. A TDNN network was successfully trained with 100% accuracy in classification for the training patterns, as well as the test patterns. The net was also robust to changes in the starting position of the Acoustic waveforms with 86% accuracy for the same test data set. In the second phase of the experiment, roadside recordings were made at a two-way urban road site in the city of Leeds with no control over the environmental parameters such as background noise, interference from other travelling vehicles, or the speed of the recorded vehicle. A second TDNN network was also successfully trained with 96% accuracy for the training patterns and 84% accuracy for the test patterns.

  • Field trial of Acoustic Signature analysis for vehicle classification
    Transportation Research Part C: Emerging Technologies, 1997
    Co-Authors: Amir Y Nooralahiyan, Denis Mckeown, Mark Dougherty, Howard R Kirby
    Abstract:

    The aim of this research is to investigate the feasibility of developing a traffic monitoring detector for the purpose of reliable on-line vehicle classification to aid traffic management systems. The detector used was a directional microphone connected to a DAT (Digital Audio Tape) recorder. The digital signal was pre-processed by LPC (Linear Predictive Coding) parameter conversion based on autocorrelation analysis. A Time Delay Neural Network (TDNN) was chosen to classify individual travelling vehicles based on their speed-independent Acoustic Signature. Locations for data acquisition included roadside recordings at a number of two-way urban road sites in the city of Leeds with no control over the environmental parameters such as background noise, interference from other travelling vehicles or the speed of the recorded vehicles. The results and performance analysis of TDNN vehicle classification, the convergence for training patterns and accuracy of test patterns are fully illustrated. The paper also provides a description of the TDNN architecture and training algorithm, and an overview of the LPC pre-processing and feature extraction technique as applied to audio monitoring of road traffic. In the final phase of the experiment, the four broad categorizations of vehicles for training the network consisted of: buses or lorries; small or large saloons; various types of motorcycles; and light goods vehicles or vans. A TDNN network was successfully trained with 94% accuracy for the training patterns and 82.4% accuracy for the test patterns.

Amir Y Nooralahiyan - One of the best experts on this subject based on the ideXlab platform.

  • Vehicle classification by Acoustic Signature
    Mathematical and Computer Modelling, 1998
    Co-Authors: Amir Y Nooralahiyan, Howard R Kirby, Denis Mckeown
    Abstract:

    The aim of this research is to investigate the feasibility of developing a traffic monitoring detector for the purpose of reliable on-line vehicle classification to aid traffic management systems. The detector used was a directional microphone connected to a DAT (Digital Audio Tape) recorder. The digital signal was preprocessed by LPC (Linear Predictive Coding) parameter conversion based on autocorrelation analysis. A Time Delay Neural Network (TDNN) was chosen to classify individual travelling vehicles based on their speed-independent Acoustic Signature. The paper provides a description of the TDNN architecture and training algorithm, and an overview of the LPC preprocessing and feature extraction technique as applied to audio monitoring of road traffic. The performance of TDNN vehicle classification, convergence, and accuracy for the training patterns are fully illustrated. To establish the viability of this classification approach, initially, recordings were carried out on a strip of airfield for four types of vehicles under controlled conditions. A TDNN network was successfully trained with 100% accuracy in classification for the training patterns, as well as the test patterns. The net was also robust to changes in the starting position of the Acoustic waveforms with 86% accuracy for the same test data set. In the second phase of the experiment, roadside recordings were made at a two-way urban road site in the city of Leeds with no control over the environmental parameters such as background noise, interference from other travelling vehicles, or the speed of the recorded vehicle. A second TDNN network was also successfully trained with 96% accuracy for the training patterns and 84% accuracy for the test patterns.

  • Field trial of Acoustic Signature analysis for vehicle classification
    Transportation Research Part C: Emerging Technologies, 1997
    Co-Authors: Amir Y Nooralahiyan, Denis Mckeown, Mark Dougherty, Howard R Kirby
    Abstract:

    The aim of this research is to investigate the feasibility of developing a traffic monitoring detector for the purpose of reliable on-line vehicle classification to aid traffic management systems. The detector used was a directional microphone connected to a DAT (Digital Audio Tape) recorder. The digital signal was pre-processed by LPC (Linear Predictive Coding) parameter conversion based on autocorrelation analysis. A Time Delay Neural Network (TDNN) was chosen to classify individual travelling vehicles based on their speed-independent Acoustic Signature. Locations for data acquisition included roadside recordings at a number of two-way urban road sites in the city of Leeds with no control over the environmental parameters such as background noise, interference from other travelling vehicles or the speed of the recorded vehicles. The results and performance analysis of TDNN vehicle classification, the convergence for training patterns and accuracy of test patterns are fully illustrated. The paper also provides a description of the TDNN architecture and training algorithm, and an overview of the LPC pre-processing and feature extraction technique as applied to audio monitoring of road traffic. In the final phase of the experiment, the four broad categorizations of vehicles for training the network consisted of: buses or lorries; small or large saloons; various types of motorcycles; and light goods vehicles or vans. A TDNN network was successfully trained with 94% accuracy for the training patterns and 82.4% accuracy for the test patterns.