Asyndetic sentences with a concretiser

Sentences with exhaustification

(1) a. What did Mary eat? b. Mary ate a pizza. c. Mary ate a pizza and a calzone. As an answer, we can think of (1b) as being ruled out by (1c), because (1c) is more exhaustive, in the sense that it contains additional true information. A number of researchers (e.g., Kuno 1972, Atlas & Levinson 1981, Horn 1981, Szabolcsi 1981, É. Kiss 1998) have noted that exhaustification effects are not limit...

Nasalance Scores of Sentences in Children with Hearing Loss

Background and purpose: Proper resonance is a major factor for the comprehension of speech in individuals with hearing loss. These people have low speech intelligibility caused by inappropriate resonance. Therefore, nasalance measurement is a principal aspect of the assessment of people with hearing loss. This study aimed at determining nasalance in children with hearing loss. Materials and me...

"Linguistic" sentences and "real" sentences

This p~$r Id~ntift~ iwe klr¢ds of sentences: "llngulsUc" sentences ~ J "r~al" a~-ntence~. "l't~,~ former is a kind of sentel~'~,e~ that ar~ often discussed in (cemputatkmal) Ungulstlc literatures, sucll as the:re In i:lgure 1. The latter, on the other hand, is a kind of senteace=~ that appear in practical applications, such as those In Flgu='e 2. Where~ts both are grammatical English sentences,...

Discriminative Training: Learning to Describe Video with Sentences, from Video Described with Sentences

We present a method for learning word meanings from complex and realistic video clips by discriminatively training (DT) positive sentential labels against negative ones, and then use the trained word models to generate sentential descriptions for new video. This new work is inspired by recent work which adopts a maximum likelihood (ML) framework to address the same problem using only positive s...

Clustering Sentences - Making Sense of Synonymous Sentences