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  • Comparative Studies. Non-European Languages/Literatures  (8)
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  • Comparative Studies. Non-European Languages/Literatures  (8)
  • Psychology  (2)
RVK
  • 1
    Online Resource
    Online Resource
    Informa UK Limited ; 2019
    In:  Clinical Linguistics & Phonetics Vol. 33, No. 3 ( 2019-03-04), p. 279-293
    In: Clinical Linguistics & Phonetics, Informa UK Limited, Vol. 33, No. 3 ( 2019-03-04), p. 279-293
    Type of Medium: Online Resource
    ISSN: 0269-9206 , 1464-5076
    RVK:
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2019
    detail.hit.zdb_id: 1485070-9
    SSG: 7,11
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  • 2
    Online Resource
    Online Resource
    Elsevier BV ; 2007
    In:  Cognition Vol. 103, No. 1 ( 2007-4), p. 80-106
    In: Cognition, Elsevier BV, Vol. 103, No. 1 ( 2007-4), p. 80-106
    Type of Medium: Online Resource
    ISSN: 0010-0277
    RVK:
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2007
    detail.hit.zdb_id: 1499940-7
    detail.hit.zdb_id: 184702-8
    SSG: 5,2
    SSG: 7,11
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  • 3
    Online Resource
    Online Resource
    Elsevier BV ; 2010
    In:  Cognition Vol. 117, No. 3 ( 2010-12), p. 348-354
    In: Cognition, Elsevier BV, Vol. 117, No. 3 ( 2010-12), p. 348-354
    Type of Medium: Online Resource
    ISSN: 0010-0277
    RVK:
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2010
    detail.hit.zdb_id: 1499940-7
    detail.hit.zdb_id: 184702-8
    SSG: 5,2
    SSG: 7,11
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  • 4
    Online Resource
    Online Resource
    Acoustical Society of America (ASA) ; 2007
    In:  The Journal of the Acoustical Society of America Vol. 121, No. 5 ( 2007-05-01), p. EL190-EL195
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 121, No. 5 ( 2007-05-01), p. EL190-EL195
    Abstract: Infants develop phonetic categories by simply being exposed to adult speech. It remains unclear, however, how they handle the extensive variability inherent to speech, and how they process multiple linguistic functions that share the same acoustic parameters. Across four neural network simulations of lexical tone acquisition, self-organizing maps were trained with continuous speech input of increasing variability. Robust tonal categorization was achieved by tracking the velocity profiles of fundamental frequency contours. This result suggests that continuous speech signal carries sufficient categorical information that can be directly processed, and that dynamic acoustic information can be used for resolving the variability problem.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    RVK:
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2007
    detail.hit.zdb_id: 1461063-2
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  • 5
    Online Resource
    Online Resource
    Acoustical Society of America (ASA) ; 2006
    In:  The Journal of the Acoustical Society of America Vol. 119, No. 5_Supplement ( 2006-05-01), p. 3420-3420
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 119, No. 5_Supplement ( 2006-05-01), p. 3420-3420
    Abstract: The surface F0 patterns of lexical tones contain variability from many different sources, which raises questions as to how infants can learn tones based on such highly variable input. A recent modeling study showed that the velocity profiles of F0 (i.e., first derivatives, or D1) enable naive learners to successfully categorize the four Mandarin tones despite cross-speaker and contextual variations [Gauthier, etal. ‘‘Recognising tones by tracking moments—How infants may develop tonal catagories from adult speech input,’’ in Proceedings ISCA workshop on plasticity in Speech Perception, edited by V. Dellwo (UCL Publications, London, UK, 2005) pp. 72–75]. The present study explores the robustness of D1 for categorizing Mandarin tones in sentences said with different focus conditions. As a contrastive communicative function, narrow focus within a multi-word utterance introduces extensive variability to F0, making tone learning a more challenging task. Using multi-speaker productions of utterances with systematically varied tones and focus [Xu, ‘‘Effects of tone and focus on the formation and alignment of contours. J. Phonet. 27, 55–105 (1999)] , self-organizing neural networks were trained with both syllable-sized D1 and F0 as input, with no special treatment for different focus conditions. In the testing phase, novel tokens were tested for tonal categorization. The results revealed that D1 yielded overall excellent categorization, far superior than F0. Detailed analyses showed that with D1, performance of tonal recognition dropped only in post-focus regions. These findings indicate that successful tone learning can be achieved with velocity profiles as input despite variability introduced by focus.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    RVK:
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2006
    detail.hit.zdb_id: 1461063-2
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  • 6
    Online Resource
    Online Resource
    Acoustical Society of America (ASA) ; 2013
    In:  The Journal of the Acoustical Society of America Vol. 134, No. 5_Supplement ( 2013-11-01), p. 4251-4251
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 134, No. 5_Supplement ( 2013-11-01), p. 4251-4251
    Abstract: Marine sediments exist universally as the lower boundary for sound propagation in ocean waveguides, and knowledge of the properties of these sediments is important for accurate modeling of sound propagation and reverberation. In order to test theory predictions of the frequency dependence of sound speed and attenuation, it is necessary to have accurate information on the sediment properties, which is most easily done in a laboratory environment. Initial results reported here were done at high frequency in a small tank, as a preliminary step before making similar low frequency measurements in a much larger tank. A sandy sediment was used and the sound speed and attenuation were measured through different thicknesses of the sample. In the frequency range of 90–170 kHz, the measured sound speed was 1757–1767 m/s, and the attenuation was 22–30 dB/m. The sound speed dispersion was found to be very weak, as expected, and much smaller than the measurement uncertainty. The attenuation was found to increase approximately linearly with frequency. The measured sound speed agrees well with Biot theory predictions, while the measured attenuation is higher than Biot predictions, most likely because the measurement include effects such as volume scattering not taken into account in the theory.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    RVK:
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2013
    detail.hit.zdb_id: 1461063-2
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  • 7
    Online Resource
    Online Resource
    Acoustical Society of America (ASA) ; 2023
    In:  The Journal of the Acoustical Society of America Vol. 153, No. 1 ( 2023-01-01), p. 538-547
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 153, No. 1 ( 2023-01-01), p. 538-547
    Abstract: Various physical characteristics, including ultrasonic waves, active acoustic emissions, vibrations, and thermal imaging, have been used for blade fault detection. In this work, we propose using the sound produced by spinning wind blades to identify faults. To the best of our knowledge, passive acoustic information has not yet been explored for this task. In particular, we develop three networks targeting different scenarios. The main contributions of this work are threefold. First, when normal and aberrant data are available for supervised learning, an attention-convolutional recurrent neural network is designed to show the feasibility of using passive sound information to conduct fault detection. Second, in the absence of abnormal training data, we build a normal-encoder network to learn the distributions of normal data through semisupervised learning, which avoids the requirement of abnormal training data. Third, when multiple devices are used to collect the data, due to different properties of devices, there is a domain mismatch issue. To overcome this, we create an adversarial domain adaptive network to close the gap between the source and target domains. Acoustic signal datasets of actual wind turbine operations are collected to evaluate our fault detection systems. The findings demonstrate that the proposed systems offer high classification accuracy and indicate the feasibility of passive acoustic signal-based wind turbine blade fault detection with one step close to automatic detection.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    RVK:
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2023
    detail.hit.zdb_id: 1461063-2
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  • 8
    Online Resource
    Online Resource
    Acoustical Society of America (ASA) ; 2005
    In:  The Journal of the Acoustical Society of America Vol. 117, No. 4_Supplement ( 2005-04-01), p. 2430-2430
    In: The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 117, No. 4_Supplement ( 2005-04-01), p. 2430-2430
    Abstract: Perception studies have shown that by the age of six months, infants show particular response patterns to tones in their native language. The present study focuses on how infants might develop lexical tones in Man- darin. F0 is generally considered the main cue in tone perception. However, F0 patterns in connected speech display extensive contextual variability. Since speech input to infants consists mainly of multi-word utterances, tone learning must involve processes that can effectively resolve variability. In this study we explore the Target Approximation model (Xu and Wang, 2001) which characterizes surface F0 as asymptotic movements toward underlying pitch targets defined as simple linear functions. The model predicts that it is possible to infer underlying pitch targets from the manners of F0 movements. Using production data of three of the speakers from Xu (1997), we trained a self-organizing neural network with both F0 profiles and F0 velocity profiles as input. In the testing phase, velocity profiles yielded far superior categorization than F0 profiles. The results confirm that velocity profiles can effectively abstract away from surface variability and directly reflect underlying articulatory goals. The finding thus points to one way through which infants can successfully derive at phonetic categories from adult speech.
    Type of Medium: Online Resource
    ISSN: 0001-4966 , 1520-8524
    RVK:
    Language: English
    Publisher: Acoustical Society of America (ASA)
    Publication Date: 2005
    detail.hit.zdb_id: 1461063-2
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