136 research outputs found
GM-TCNet: Gated Multi-scale Temporal Convolutional Network using Emotion Causality for Speech Emotion Recognition
In human-computer interaction, Speech Emotion Recognition (SER) plays an
essential role in understanding the user's intent and improving the interactive
experience. While similar sentimental speeches own diverse speaker
characteristics but share common antecedents and consequences, an essential
challenge for SER is how to produce robust and discriminative representations
through causality between speech emotions. In this paper, we propose a Gated
Multi-scale Temporal Convolutional Network (GM-TCNet) to construct a novel
emotional causality representation learning component with a multi-scale
receptive field. GM-TCNet deploys a novel emotional causality representation
learning component to capture the dynamics of emotion across the time domain,
constructed with dilated causal convolution layer and gating mechanism.
Besides, it utilizes skip connection fusing high-level features from different
gated convolution blocks to capture abundant and subtle emotion changes in
human speech. GM-TCNet first uses a single type of feature, mel-frequency
cepstral coefficients, as inputs and then passes them through the gated
temporal convolutional module to generate the high-level features. Finally, the
features are fed to the emotion classifier to accomplish the SER task. The
experimental results show that our model maintains the highest performance in
most cases compared to state-of-the-art techniques.Comment: The source code is available at:
https://github.com/Jiaxin-Ye/GM-TCNe
Trade-Offs between the Metabolic Rate and Population Density of Plants
The energetic equivalence rule, which is based on a combination of metabolic theory and the self-thinning rule, is one of the fundamental laws of nature. However, there is a progressively increasing body of evidence that scaling relationships of metabolic rate vs. body mass and population density vs. body mass are variable and deviate from their respective theoretical values of 3/4 and β3/4 or β2/3. These findings questioned the previous hypotheses of energetic equivalence rule in plants. Here we examined the allometric relationships between photosynthetic mass (Mp) or leaf mass (ML) vs. body mass (Ξ²); population density vs. body mass (Ξ΄); and leaf mass vs. population density, for desert shrubs, trees, and herbaceous plants, respectively. As expected, the allometric relationships for both photosynthetic mass (i.e. metabolic rate) and population density varied with the environmental conditions. However, the ratio between the two exponents was β1 (i.e. Ξ²/Ξ΄β=ββ1) and followed the trade-off principle when local resources were limited. Our results demonstrate for the first time that the energetic equivalence rule of plants is based on trade-offs between the variable metabolic rate and population density rather than their constant allometric exponents
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