Time Series Motif Discovery (TSMD) is defined as searching for patterns that are previously unknown and appear with a given frequency in time series. Another problem strongly related with TSMD is Word Segmentation. This problem has received much attention from the community that studies early language acquisition in babies and toddlers. The development of biologically plausible models for word segmentation could greatly advance this field. Therefore, in this article, we propose the Variable Input Length Map (VILMAP) for Motif Discovery and Word Segmentation. The model is based on the Self-Organizing Maps and can identify Motifs with different lengths in time series. In our experiments, we show that VILMAP presents good results in finding Motifs in a standard Motif discovery dataset and can avoid catastrophic forgetting when trained with datasets with increasing values of input size. We also show that VILMAP achieves results similar or superior to other methods in the literature developed for the task of word segmentation.
Unlike the spacing provided in the written text, the spoken words are rarely delimited by pauses, so children must learn somehow to identify the boundaries between words as they hear the sentences. Because the structure of words is significantly variable in all languages, it is difficult to know how a child between 9 and 15 months of age achieve this ability. Therefore, segmentation is a key step in language acquisition, specifically in lexical development @cite_25 . It is worth pointing out that finding the exact boundaries of all words in a sentence is not strictly necessary for children to understand what is said. They actually need to recognize the words present in the sentence (simple or compound) in the correct order, what can be done despite the occurrence of certain boundary detection errors, as it is observed in young children @cite_28 .
@cite_28 @cite_25
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An important element of learning to read and write at school is the ability to define word boundaries. Defining word boundaries in text writing is not a straightforward task even for children who have mastered graphophonemic correspondences. In children’s writing, unconventional word segmentation has been observed across a range of languages and contexts with more occurrences of hyposegmentation (failure to separate two or more written words with a space) than hypersegmentation (written words are split into more than one segment). However, it is still unclear how frequent these errors are and the relationships of these written error patterns to the child’s development in oral language, spelling and reading remains relatively unexplored. To address these issues, unconventional written lexical segmentations in Brazilian Portuguese children’s text production during their first years at primary school (Year 1 to Year 3) were examined in relation to different cognitive and linguistic measures and patterns of spelling errors. Results reveal that in Portuguese the establishment of word boundaries in written text is not explained by visuospatial skills or limitations in processing resources (working memory). In contrast higher occurrences of hyposegmentation patterns were associated with lower levels of reading, vocabulary, verbal ability and morphological awareness whereas hypersegmentations were rarer and related to lower levels of reading and morphological awareness and typically only occurred in the initial stages of learning to write (Year 1). Occurrences of hyposegmentations as well as hypersegmentations were also related to spelling errors which reflected children’s poor phonological skills. Abstract Groups of 32 children in each of three grades (kindergarten, second, and fourth) listened to a man's voice and a woman's voice, speaking words simultaneously. On one run through the 23 pairs of words, Ss were instructed to report what the man's voice was saying; on another, the words spoken by the woman. The stimulus words were systematically varied with respect to the number of syllables they contained. For cach S, the stimulus words were presented on one occasion binaurally (both words in both cars), on another occasion, dichotically (two different words in each ear). The number of correct reports of the word spoken by the desired voice increased with age; the number of intrusive errors (reports of words spoken by the unwanted voice) declined with age. At all age levels, scores were higher under dichotic presentation, but there was no change with age in the advantage derived from this presentation. Children at each age level made more errors on single-syllable than on multi-syllable words, but this difference was greater for older children. An analysis of errors revealed systematic differences among age groups in the nature of wrong guesses. Performanec improved through blocks of trials, at all age levels. Abstract We ask if certain dimensions of perceptual similarity are weighted more heavily than others in determining word extension. The specific dimensions examined were shape, size, and texture. In four experiments, subjects were asked either to extend a novel count noun to new instances or, in a nonword classification task, to put together objects that go together. The subjects were 2-year-olds, 3-year-olds, and adults. The results of all four experiments indicate that 2- and 3-year-olds and adults all weight shape more heavily than they do size or texture. This observed emphasis on shape, however, depends on the age of the subject and the task. First, there is a developmental trend. The shape bias increases in strength and generality from 2 to 3 years of age and more markedly from early childhood to adulthood. Second, in young children, the shape bias is much stronger in word extension than in nonword classification tasks. These results suggest that the development of the shape bias originates in language learning—it reflects a fact about language—and does not stem from general perceptual processes. This paper presents several acoustic analyses carried out on read speech collected from Italian children aged from 7 to 13 years and North American children aged from 5 to 17 years. These analyses aimed at achieving a better understanding of spectral and temporal changes in speech produced by children of various ages in view of the development of automatic speech recognition applications. The results of these analyses confirm and complement the results reported in the literature, showing that characteristics of children's speech change with age and that spectral and temporal variability decrease as age increases. In fact, younger children show a substantially higher intra- and inter-speaker variability with respect to older children and adults. We investigated the use of several methods for speaker adaptive acoustic modeling to cope with inter-speaker spectral variability and to improve recognition performance for children. These methods proved to be effective in recognition of read speech with a vocabulary of about 11k words.