In the high noise condition, verb-noun sentences were presented during auditory background noise (white noise, 78 dB), and in the low noise condition sentences were presented without noise.
Here, the value 0.4 in the condition sentence is selected to distinguish different areas containing fine details from those showing a uniform pattern.
Sentence intelligibility scores confirmed variations between languages, but these variations were statistically significant only at the STI = 0.4 condition (sentence tests being less sensitive to very good and very poor room acoustic conditions).
Figure 3 shows reading speed as a function of text size for the three conditions: MNREAD sentences (red curves, legend MN), sentence generator sentences scored by marking the number of words read correctly (green curves, SG) and the sentence generator sentences with true/false scoring (bue curves, TF in the legend).
So we can sensibly talk about the meaning of a non-sentential constituent of the language, but these meanings are derived from the truth conditions of sentences, rather than determining the meanings of sentences.
The self-condition is subdivided into four conditions (15 sentences per condition): a 'negative' mental condition (for example sentences as 'I am insensible', 'I forget important things'), a 'positive' mental condition ('I am intelligent', 'I am honest'.), a negative physical condition ('I am often ill', 'I am fat'), and a positive physical condition ('I am strong', 'I am healthy).
For instance, the first formal proposal for truth conditions of sentences in the past progressive stated that a sentence S in the past progressive is true if and only if there exists an open interval before the speech time at which the sentence without the progressive is true.
Consider, for example, the attempt to state the truth conditions of sentences of the form 'It is necessary that S' and 'It is possible that S' (where S is any sentence).
Stories about hellish conditions, draconian sentences, physical brutality and the neglect of rehabilitation saturate the news media.
