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In future weeks we'll delve into more ways you can play with subjects and predicates, but first, in the next few lessons I will write, we'll explore the raw materials of sentence-building: nouns, adjectives and verbs.
First, the taggers used are tuned for analyzing full sentences, but most of the input material consists of sentence fragments or noun phrases which gives the tagging a higher error rate than usual.
Further results revealed that (a) superimposing the prosodic structure of one dialect (Bern Swiss German) onto another (Valais Swiss German) caused greater variability across some listeners than the other way around and that (b) identification performance varies as a function of sentence material used, i.e. how the sentences differ in segmental and prosodic make-up.
For most of the assessments in this domain, it is essential to aggregate information: For example, when assessing the length of a sentence, the assessor must search the entire health information material for sentences that are too long.
This is because we expected no intrusion of syntactical sentence external material into sentence processing, precluding any interaction.
For all the day, though, you sense, he is a writer, writing like a sculptor, in that he creates a mass of material and then happily, passionately, brilliantly takes away, takes away, swirl of sentence by swirl of sentence.
But it represents how related one word is to every other word in the vast dictionary of training materials (2.5 billion sentence pairs for English and French; 500 million for English and Chinese).
Here, we investigated how the semantic relatedness of sentence constituents influences sentence processing.
Evaluations and tests were realized with the speech material in the form of sentences of male and female speakers expressing four emotional states (joy, sadness, anger, and a neutral state) in Czech and Slovak languages.
The materials of word segmentation tasks are at least phrases, but we prefer naturally occurred sentences.
Our previous study had tested the effects of sentence-extraneous material on within-sentence processing only for the same type of information, that is, semantic-semantic and syntactic-syntactic interactions.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com