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A lot of robust speech recognition approaches have been proposed to reduce the acoustic mismatch in the past few decades and most of them can be categorized into feature compensation, model adaptation, and uncertainty-based approaches [2].
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Visual-based environmental cues can be categorized into features (e.g. colour or pattern) or geometry (e.g. distance or direction).
Individuals with autism or ID also manifesting more than one comorbid feature were categorized into 'multiple features' or 'multiple OHI features' categories.
Strictly speaking, dimension reduction algorithms can be categorized into two groups: feature extraction and feature selection.
The positive and negative features of the two favorite options were categorized into five "Sought" features and five "Avoided" features.
Due to alternative TSS and splicing, a given probe could be categorized into several gene feature categories.
These DFD features are categorized into logic DFD (LDFD) features, which enable the nonintrusive isolation of failures, and physical DFD (PDFD) features, which enable physically intrusive analysis.
The approaches of protein function prediction can be categorized into two categories, feature-based methods and graph-based methods, in terms of input data and methodology.
Features are broadly categorized into structural and statistical features.
Semantic roles/relations may categorize into different feature dimensions.
These features can be categorized into two groups: frame-averaged features, including the mean values of pitch, energy and duration; and TILT features provided by parameterizing the pitch contour using the TILT model.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com