Voice processing abilities in children with autism, children with specific language impairments and young typically developing children

It is well established that people with autism have impaired face processing, but much less is known about voice processing in autism. Four experiments were therefore carried out to assess (1) familiar voice-face and sound-object matching; (2) familiar voice recognition; (3) unfamiliar voice discrimination; and (4) vocal affect naming and vocal-facial affect matching. In Experiments 1 and 2 language-matched children with specific language impairment (SLI) were the controls. In Experiments 3 and 4 language-matched children with SLI and young mainstream children were the controls. The results were unexpected: the children with autism were not impaired relative to controls on Experiments 1, 2 and 3, and were superior to the children with SLI on both parts of Experiment 4, although impaired on affect matching relative to the mainstream children. These results are interpreted in terms of an unexpected impairment of voice processing in the children with SLI associated partly, but not wholly, with an impairment of cross-modal processing. Performance on the experimental tasks was not associated with verbal or nonverbal ability in either of the clinical groups. The implications of these findings for understanding autism and SLI are discussed

Multilingual Schema Matching for Wikipedia Infoboxes

Recent research has taken advantage of Wikipedia's multilingualism as a resource for cross-language information retrieval and machine translation, as well as proposed techniques for enriching its cross-language structure. The availability of documents in multiple languages also opens up new opportunities for querying structured Wikipedia content, and in particular, to enable answers that straddle different languages. As a step towards supporting such queries, in this paper, we propose a method for identifying mappings between attributes from infoboxes that come from pages in different languages. Our approach finds mappings in a completely automated fashion. Because it does not require training data, it is scalable: not only can it be used to find mappings between many language pairs, but it is also effective for languages that are under-represented and lack sufficient training samples. Another important benefit of our approach is that it does not depend on syntactic similarity between attribute names, and thus, it can be applied to language pairs that have distinct morphologies. We have performed an extensive experimental evaluation using a corpus consisting of pages in Portuguese, Vietnamese, and English. The results show that not only does our approach obtain high precision and recall, but it also outperforms state-of-the-art techniques. We also present a case study which demonstrates that the multilingual mappings we derive lead to substantial improvements in answer quality and coverage for structured queries over Wikipedia content.Comment: VLDB201

Where did Words Come from? A Linking Theory of Sound Symbolism and Natural Language Evolution

Where did words come from? The traditional view is that the relation between the sound of a word and its meaning is arbitrary. An alternative hypothesis, known as sound symbolism, holds that form-meaning correspondence is systematic. Numerous examples of sound symbolism exist across natural language phyla. Moreover, cross-linguistic similarities suggest that sound symbolism represents a language universal. For example, many unrelated languages affix an "ee" sound to words in order to emphasize size distinctions or express affection (e.g., look at the teeny weeny baby); other such phonetic universals are evident for object mass, color, brightness, and aggression. We hypothesize that sound symbolism reflects sensitivity to an ecological law (i.e., Hooke's Law) governing an inverse relation between object mass and acoustic resonance. In two experiments healthy adults showed high agreement in matching pure tones to color swatches and nonwords to novel objects as linear functions of frequency and luminance. These results support a degree of non-arbitrariness in integrating visual and auditory information. We discuss implications for sound symbolism as a factor underlying language evolution