Prosody structures utterances, indicates sentence modality (linguistic prosody) and expresses the speaker's intention, attitude and emotions (affective prosody).
Again, the classification was carried out by HMMs, which model the prosodic contour for each clause and/or sentence modality type.
Based on the literature, we expect a primary role for F0 and a secondary role for duration in the perception of sentence modality contrasts.
A subsequent perception study, designed to test to what extent these prosodic cues to sentence modality are used in perception, found that (a) pitch register and (b) the placement of peak on a particular syllable both affect listeners' judgments.
Hence, intonemes in the original sense mainly distinguish sentence modality, although there exists a variant of the I↓ intoneme, I E)↓ which denotes emphatic accentuation and occurs in contrastive, narrowly focused environments.
We used a 2 × 2 × 2 × 2 design with the factors Syntactic Repetition (syntax was novel vs. repeated compared with the sentence that preceded it), Modality Repetition (processing modality, i.e., speaking vs. listening was novel vs. repeated compared with the sentence that preceded it), Target Modality (listening vs. speaking), and Target Structure (active vs. passive voice).
While coding, linguistic cues such as modality (modals, adverbs), sentence structure and subjects, and reporting verbs were accounted for.
One extension is to add a binary modality ⊳, where for a given arithmetical theory T, the modal sentence A ⊳ B is meant to stand for "T+B is interpretable in T+A".
For further syntactic and semantic level processing of the input speech in ASR, clause and sentence boundary detection and modality (sentence type) recognition was implemented.
Each anomaly-sensitive ROI showed the same pattern of response across sentence types in each modality.
