Quantitative and Qualitative Analysis of Experience in Acquisition of a Miniature Artificial Language

Nagata, Hiroshi

doi:10.4992/psycholres1954.18.174

Cited by 7 publications

(11 citation statements)

References 30 publications

(37 reference statements)

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“…One account of the present results is based on the observation that the variations in synthetic speech that must be learned are lawful and rule-governed much as the variations in artificial-language materials are (e.g., Nagata, 1976;Palermo & Parish, 1971). Under these conditions, learning of a repeated training set appears to produce the same level of generalization as does training with novel stimuli as long as the number of presentations is the same for the two training procedures.…”

Section: Resultsmentioning

confidence: 99%

“…Based on earlier research in pattern learning (e.g., Dukes & Bevan, 1967;Posner & Keele, 1968), subjects trained on novel exemplars should show more improvement than do those trained with repeated exemplars, because the novel training set provides a broader sample of the acoustic-phonetic variability in Votrax speech than is provided by the repeated training set. However, from artificial-language learning studies (e.g., Nagata, 1976;Palermo & Parish, 1971), we predict that if the repeated training set sufficiently characterizes the underlying acoustic-phonetic structure of the synthetic speech, there should be no performance difference between subjects receiving repeated training stimuli and those presented with novel training stimuli (as long as both sets of subjects receive an equal number of exemplars).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Perceptual learning of synthetic speech produced by rule.

Greenspan¹,

Nusbaum²,

Pisoni³

1988

Journal of Experimental Psychology: Learning, Memory, and Cogni

109

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To examine the effects of stimulus structure and variability on perceptual learning, we compared transcription accuracy before and after training with synthetic speech produced by rule. Subjects were trained with either isolated words or fluent sentences of synthetic speech that were either novel stimuli or a fixed list of stimuli that was repeated. Subjects who were trained on the same stimuli every day improved as much as did the subjects who were given novel stimuli. In a second experiment, the size of the repeated stimulus set was reduced. Under these conditions, subjects trained with repeated stimuli did not generalize to novel stimuli as well as did subjects trained with novel stimuli. Our results suggest that perceptual learning depends on the degree to which the training stimuli characterize the underlying structure of the full stimulus set. Furthermore, we found that training with isolated words only increased the intelligibility of isolated words, although training with sentences increased the intelligibility of both isolated words and sentences.Speech signals provide an especially interesting and important class of stimuli for studying the effect of stimulus variability on perceptual learning, primarily because of the lack of acoustic-phonetic invariance of the speech signal (e.g., Liberman, Cooper, Shankweiler, & Studdert-Kennedy, 1967). Despite large differences in the acoustic-phonetic structure of speech produced by different talkers, listeners seldom have any difficulty recognizing the speech produced by a novel talker. Although context-dependent and talker-dependent acoustic-phonetic variability has often been viewed as noise that must be stripped away from the speech signal in order to reveal invariant phonetic structures (e.g., Stevens & Blumstein, 1978), it is also possible that this variability serves as an important source of information for the listener, which indicates structural relations among acoustic cues as well as information about the talker . If the sources of variability in the speech waveform are understood by the listener, this information may play an important role in the perceptual decoding of linguistic segments (see Liberman, 1970). Therefore, if a listener must learn to recognize speech that is either degraded or impoverished, information about acoustic-phonetic variability of the speech signal may be critical to the learning process. Schwab, Nusbaum, and Pisoni (1985) recently demonstrated that moderate amounts of training with low-intelligibility synthetic speech will improve word recognition performance for novel stimuli generated by the same text-to-speech system. Schwab et al. trained subjects by presenting synthetic speech followed by immediate feedback in recognition tasks for words in isolation, for words in fluent meaningful sentences, and for words in fluent semantically anomalous sentences. Subjects trained under these conditions improved significantly in recognition performance for synthetic words in isolation and in sentence contexts compared to subjec...

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Perceptual learning of synthetic speech produced by rule.

Greenspan¹,

Nusbaum²,

Pisoni³

1988

Journal of Experimental Psychology: Learning, Memory, and Cogni

109

View full text Add to dashboard Cite

show abstract

“…The presence of semantic information has been proposed to affect the learning (Moeser and Bregman, 1972 ; Amato and MacDonald, 2010 ; Poletiek and Lai, 2012 ; Poletiek and Monaghan, unpublished manuscript) and processing (Howard and Ballas, 1980 ; Spivey et al, 2002 ) of complex structures in natural language. Making exemplars meaningful by adding a reference field (e.g., visual illustrations of scenes they refer to) has often been shown to enhance the learning of phrase structure grammars, which specify the relations between classes of elements (Nagata, 1976 ; Mori and Moeser, 1983 ; Meier and Bower, 1986 ; Valian and Coulson, 1988 ; Amato and MacDonald, 2010 ; see also Van den Bos et al, 2012 ). Moreover, two such studies have shown that the presence of a visual reference field can compensate negative effects of complexity of the grammar (Moeser and Bregman, 1972 ; Nagata, 1977 ).…”

Section: Introductionmentioning

confidence: 99%

Learning simple and complex artificial grammars in the presence of a semantic reference field: effects on performance and awareness

Bos

Poletiek

2015

Front. Psychol.

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This study investigated whether the negative effect of complexity on artificial grammar learning could be compensated by adding semantics. Participants were exposed to exemplars from a simple or a complex finite state grammar presented with or without a semantic reference field. As expected, performance on a grammaticality judgment test was higher for the simple grammar than for the complex grammar. For the simple grammar, the results also showed that participants presented with a reference field and instructed to decode the meaning of each exemplar (decoding condition) did better than participants who memorized the exemplars without semantic referents (memorize condition). Contrary to expectations, however, there was no significant difference between the decoding condition and the memorize condition for the complex grammar. These findings indicated that the negative effect of complexity remained, despite the addition of semantics. To clarify how the presence of a reference field influenced the learning process, its effects on the acquisition of two types of knowledge (first- and second-order dependencies) and on participants' awareness of their knowledge were examined. The results tentatively suggested that the reference field enhanced the learning of second-order dependencies. In addition, participants in the decoding condition realized when they had knowledge relevant to making a grammaticality judgment, whereas participants in the memorize condition demonstrated some knowledge of which they were unaware. These results are in line with the view that the reference field enhanced structure learning by making certain dependencies more salient. Moreover, our findings stress the influence of complexity on artificial grammar learning.

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“…These results clearly indicate that language acquisition may be mediated by nonlinguistic semantic aspects of a context. Nagata (1976), on the other hand, showed not only that semantic reference facilitated overall acquisition of the syn-tax, but that syntax acquisition also occurred for some subjects who were not given semantic reference. Since the complexity of syntax utilized by Moeser and Bregman (1972) and Nagata (1976) differed considerably, Nagata (1976) suggested that as the complexity of syntax increases the presence of semantic reference becomes necessary.…”

Section: The Interaction Between Syntactic Complexity and Semantic Re...mentioning

confidence: 93%

“…Nagata (1976), on the other hand, showed not only that semantic reference facilitated overall acquisition of the syn-tax, but that syntax acquisition also occurred for some subjects who were not given semantic reference. Since the complexity of syntax utilized by Moeser and Bregman (1972) and Nagata (1976) differed considerably, Nagata (1976) suggested that as the complexity of syntax increases the presence of semantic reference becomes necessary. This implies that whether semantic reference is necessary or not for syntax acquisition depends on a level of syntactic complexity.…”

Section: The Interaction Between Syntactic Complexity and Semantic Re...mentioning

confidence: 93%

Quantitative and Qualitative Analysis of Experience in Acquisition of a Miniature Artificial Language

Cited by 7 publications

References 30 publications

Perceptual learning of synthetic speech produced by rule.

Perceptual learning of synthetic speech produced by rule.

Learning simple and complex artificial grammars in the presence of a semantic reference field: effects on performance and awareness

The Interaction Between Syntactic Complexity and Semantic Reference in Acquisition of a Miniature Artificial Language

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