The Experts below are selected from a list of 64539 Experts worldwide ranked by ideXlab platform

Gentaro Taga - One of the best experts on this subject based on the ideXlab platform.

  • Treadmill Experience Alters Treadmill Effects on Perceived Visual Motion
    PloS one, 2011
    Co-Authors: Yoshiko Yabe, Hama Watanabe, Gentaro Taga
    Abstract:

    Information on ongoing body movements can affect the perception of ambiguous visual motion. Previous studies on “treadmill capture” have shown that treadmill walking biases the perception of ambiguous apparent motion in backward direction in accordance with the optic flow during normal walking, and that long-term treadmill experience changes the effect of treadmill capture. To understand the underlying mechanisms for these phenomena, we Conducted Experiment 1 with non-treadmill runners and Experiment 2 with treadmill runners. The participants judged the motion direction of the apparent motion stimuli of horizontal gratings in front of their feet under three conditions: walking on a treadmill, standing on a treadmill, and standing on the floor. The non-treadmill runners showed the presence of downward bias only under the walking condition, indicating that ongoing treadmill walking but not the awareness of being on a treadmill biased the visual directional discrimination. In contrast, the treadmill runners showed no downward bias under any of the conditions, indicating that neither ongoing activity nor the awareness of spatial context produced perception bias. This suggests that the long-term repetitive experience of treadmill walking without optic flow induced the formation of a treadmill-specific locomotor-visual linkage to perceive the complex relationship between self and the environment.

Xiaoqi Wang - One of the best experts on this subject based on the ideXlab platform.

  • insights in to end learning scheme for language identification
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Weicheng Cai, Zexin Cai, Wenbo Liu, Xiaoqi Wang
    Abstract:

    A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically. In the end-to-end pipeline, a general encoding layer is employed on top of the frontend CNN, so that it can encode the variable-length input sequence into an utterance level vector automatically. After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline. We further introduce a general encoding layer, illustrating the reason why they might be appropriate for language identification. We elaborate on several typical encoding layers, including a temporal average pooling layer, a recurrent encoding layer and a novel learnable dictionary encoding layer. We Conducted Experiment on NIST LRE07 closed-set task, and the results show that our proposed end-to-end systems achieve state-of-the-art performance.

  • Insights into End-to-End Learning Scheme for Language Identification
    arXiv: Audio and Speech Processing, 2018
    Co-Authors: Weicheng Cai, Zexin Cai, Wenbo Liu, Xiaoqi Wang
    Abstract:

    A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically. In the end-to-end pipeline, a general encoding layer is employed on top of the front-end CNN, so that it can encode the variable-length input sequence into an utterance level vector automatically. After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline. We further introduce a general encoding layer, illustrating the reason why they might be appropriate for language identification. We elaborate on several typical encoding layers, including a temporal average pooling layer, a recurrent encoding layer and a novel learnable dictionary encoding layer. We Conducted Experiment on NIST LRE07 closed-set task, and the results show that our proposed end-to-end systems achieve state-of-the-art performance.

  • ICASSP - Insights in-to-End Learning Scheme for Language Identification
    2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018
    Co-Authors: Weicheng Cai, Zexin Cai, Wenbo Liu, Xiaoqi Wang
    Abstract:

    A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically. In the end-to-end pipeline, a general encoding layer is employed on top of the frontend CNN, so that it can encode the variable-length input sequence into an utterance level vector automatically. After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline. We further introduce a general encoding layer, illustrating the reason why they might be appropriate for language identification. We elaborate on several typical encoding layers, including a temporal average pooling layer, a recurrent encoding layer and a novel learnable dictionary encoding layer. We Conducted Experiment on NIST LRE07 closed-set task, and the results show that our proposed end-to-end systems achieve state-of-the-art performance.

Yoshiko Yabe - One of the best experts on this subject based on the ideXlab platform.

  • Treadmill Experience Alters Treadmill Effects on Perceived Visual Motion
    PloS one, 2011
    Co-Authors: Yoshiko Yabe, Hama Watanabe, Gentaro Taga
    Abstract:

    Information on ongoing body movements can affect the perception of ambiguous visual motion. Previous studies on “treadmill capture” have shown that treadmill walking biases the perception of ambiguous apparent motion in backward direction in accordance with the optic flow during normal walking, and that long-term treadmill experience changes the effect of treadmill capture. To understand the underlying mechanisms for these phenomena, we Conducted Experiment 1 with non-treadmill runners and Experiment 2 with treadmill runners. The participants judged the motion direction of the apparent motion stimuli of horizontal gratings in front of their feet under three conditions: walking on a treadmill, standing on a treadmill, and standing on the floor. The non-treadmill runners showed the presence of downward bias only under the walking condition, indicating that ongoing treadmill walking but not the awareness of being on a treadmill biased the visual directional discrimination. In contrast, the treadmill runners showed no downward bias under any of the conditions, indicating that neither ongoing activity nor the awareness of spatial context produced perception bias. This suggests that the long-term repetitive experience of treadmill walking without optic flow induced the formation of a treadmill-specific locomotor-visual linkage to perceive the complex relationship between self and the environment.

Weicheng Cai - One of the best experts on this subject based on the ideXlab platform.

  • insights in to end learning scheme for language identification
    International Conference on Acoustics Speech and Signal Processing, 2018
    Co-Authors: Weicheng Cai, Zexin Cai, Wenbo Liu, Xiaoqi Wang
    Abstract:

    A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically. In the end-to-end pipeline, a general encoding layer is employed on top of the frontend CNN, so that it can encode the variable-length input sequence into an utterance level vector automatically. After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline. We further introduce a general encoding layer, illustrating the reason why they might be appropriate for language identification. We elaborate on several typical encoding layers, including a temporal average pooling layer, a recurrent encoding layer and a novel learnable dictionary encoding layer. We Conducted Experiment on NIST LRE07 closed-set task, and the results show that our proposed end-to-end systems achieve state-of-the-art performance.

  • Insights into End-to-End Learning Scheme for Language Identification
    arXiv: Audio and Speech Processing, 2018
    Co-Authors: Weicheng Cai, Zexin Cai, Wenbo Liu, Xiaoqi Wang
    Abstract:

    A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically. In the end-to-end pipeline, a general encoding layer is employed on top of the front-end CNN, so that it can encode the variable-length input sequence into an utterance level vector automatically. After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline. We further introduce a general encoding layer, illustrating the reason why they might be appropriate for language identification. We elaborate on several typical encoding layers, including a temporal average pooling layer, a recurrent encoding layer and a novel learnable dictionary encoding layer. We Conducted Experiment on NIST LRE07 closed-set task, and the results show that our proposed end-to-end systems achieve state-of-the-art performance.

  • ICASSP - Insights in-to-End Learning Scheme for Language Identification
    2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018
    Co-Authors: Weicheng Cai, Zexin Cai, Wenbo Liu, Xiaoqi Wang
    Abstract:

    A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically. In the end-to-end pipeline, a general encoding layer is employed on top of the frontend CNN, so that it can encode the variable-length input sequence into an utterance level vector automatically. After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline. We further introduce a general encoding layer, illustrating the reason why they might be appropriate for language identification. We elaborate on several typical encoding layers, including a temporal average pooling layer, a recurrent encoding layer and a novel learnable dictionary encoding layer. We Conducted Experiment on NIST LRE07 closed-set task, and the results show that our proposed end-to-end systems achieve state-of-the-art performance.

Alvin W. Smith - One of the best experts on this subject based on the ideXlab platform.

  • serologic evidence of vesivirus specific antibodies associated with abortion in horses
    American Journal of Veterinary Research, 2006
    Co-Authors: Andreas Kurth, Douglas E Skilling, Alvin W. Smith
    Abstract:

    Objective—To test horses for serologic evidence of an association between vesiviral antibodies and abortion. Sample Population—Sera from 141 horses. Procedures—2 Experiments were Conducted. Experiment 1 comprised sera obtained in 2001 and 2002 from 3 groups of horses (58 mares from farms with a history of abortion problems, 25 mares between 3 and 13 years of age with unknown reproductive histories that were sold at auction [breeding-age control mares], and 29 mixed-age males and yearling females sold at auction [negative control population]). Experiment 2 comprised sera from 3 groups of pregnant mares (10 pregnant mares fed Eastern tent caterpillars [ETCs], 9 pregnant mares fed ETC frass only, and 10 pregnant control mares). Sera were analyzed for antibodies against vesivirus by use of a validated recombinant vesivirusspecific peptide antigen in an indirect ELISA. Results—For Experiment 1, 37 of 58 (63.8%) mares from farms with abortion problems were seropositive for vesivirus antibodies, whereas 10 of 25...

  • serologic evidence of vesivirus specific antibodies associated with abortion in horses
    American Journal of Veterinary Research, 2006
    Co-Authors: Andreas Kurth, Douglas E Skilling, Alvin W. Smith
    Abstract:

    Objective—To test horses for serologic evidence of an association between vesiviral antibodies and abortion. Sample Population—Sera from 141 horses. Procedures—2 Experiments were Conducted. Experiment 1 comprised sera obtained in 2001 and 2002 from 3 groups of horses (58 mares from farms with a history of abortion problems, 25 mares between 3 and 13 years of age with unknown reproductive histories that were sold at auction [breeding-age control mares], and 29 mixed-age males and yearling females sold at auction [negative control population]). Experiment 2 comprised sera from 3 groups of pregnant mares (10 pregnant mares fed Eastern tent caterpillars [ETCs], 9 pregnant mares fed ETC frass only, and 10 pregnant control mares). Sera were analyzed for antibodies against vesivirus by use of a validated recombinant vesivirusspecific peptide antigen in an indirect ELISA. Results—For Experiment 1, 37 of 58 (63.8%) mares from farms with abortion problems were seropositive for vesivirus antibodies, whereas 10 of 25...