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In order for children to understand and reason about the world in an adult-like fashion, they nee... more In order for children to understand and reason about the world in an adult-like fashion, they need to learn that conceptual categories are organized in a hierarchical fashion (e.g., a dog is also an animal). While children learn from their first-hand observation of the world, social knowledge transmission via language can also play an important role in this learning. Previous studies have documented several cues in parental talk that can help children learn about conceptual hierarchy. However, these studies have used different datasets and methods which has made it difficult to compare the relative usefulness of various linguistic cues to conceptual knowledge and to test whether they scale up to naturalistic speech. Here, we study a large-scale corpus of English child-directed speech and used a unified classification-based evaluation method which allowed us to investigate and compare cues that vary in terms of how explicit the information they offer is. We found the more explicit cu...
In this study, we replicate the text-adaptive generative adversarial network proposed in [4]. We ... more In this study, we replicate the text-adaptive generative adversarial network proposed in [4]. We do this for two reasons: first, image modification with natural language is an interesting and challenging problem, and second, replicating studies can provide additional information about the vailidity and generalizability of the original authors’ claims. Our replication followed the specifications of the network given in the published study and supplementary materials (and not the publicly available code provided by the authors) and we trained our network using the CUB [9] dataset. We evaluated our network using L2 error and informal qualitative measures and found that our results were significantly worse than the results from the original study, due to issues in accurately and comprehensively recreating the network.
In order for children to understand and reason about the world in a mature fashion, they need to ... more In order for children to understand and reason about the world in a mature fashion, they need to learn that conceptual categories are organized in a hierarchical fashion (e.g., a dog is also an animal). The caregiver linguistic input can play an important role in this learning, and previous studies have documented several cues in parental talk that can help children learn a conceptual hierarchy. However, these previous studies used different datasets and methods which made difficult the systematic comparison of these cues and the study of their relative contribution. Here, we use a large-scale corpus of child-directed speech and a classification-based evaluation method which allowed us to investigate, within the same framework, various cues that varied radically in terms of how explicit the information they offer is. We found the most explicit cues to be too sparse or too noisy to support robust learning (though part of the noise may be due to imperfect operationalization). In contr...
In order for children to understand and reason about the world in an adult-like fashion, they nee... more In order for children to understand and reason about the world in an adult-like fashion, they need to learn that conceptual categories are organized in a hierarchical fashion (e.g., a dog is also an animal). While children learn from their first-hand observation of the world, social knowledge transmission via language can also play an important role in this learning. Previous studies have documented several cues in parental talk that can help children learn about conceptual hierarchy. However, these studies have used different datasets and methods which has made it difficult to compare the relative usefulness of various linguistic cues to conceptual knowledge and to test whether they scale up to naturalistic speech. Here, we study a large-scale corpus of English child-directed speech and used a unified classification-based evaluation method which allowed us to investigate and compare cues that vary in terms of how explicit the information they offer is. We found the more explicit cu...
In this study, we replicate the text-adaptive generative adversarial network proposed in [4]. We ... more In this study, we replicate the text-adaptive generative adversarial network proposed in [4]. We do this for two reasons: first, image modification with natural language is an interesting and challenging problem, and second, replicating studies can provide additional information about the vailidity and generalizability of the original authors’ claims. Our replication followed the specifications of the network given in the published study and supplementary materials (and not the publicly available code provided by the authors) and we trained our network using the CUB [9] dataset. We evaluated our network using L2 error and informal qualitative measures and found that our results were significantly worse than the results from the original study, due to issues in accurately and comprehensively recreating the network.
In order for children to understand and reason about the world in a mature fashion, they need to ... more In order for children to understand and reason about the world in a mature fashion, they need to learn that conceptual categories are organized in a hierarchical fashion (e.g., a dog is also an animal). The caregiver linguistic input can play an important role in this learning, and previous studies have documented several cues in parental talk that can help children learn a conceptual hierarchy. However, these previous studies used different datasets and methods which made difficult the systematic comparison of these cues and the study of their relative contribution. Here, we use a large-scale corpus of child-directed speech and a classification-based evaluation method which allowed us to investigate, within the same framework, various cues that varied radically in terms of how explicit the information they offer is. We found the most explicit cues to be too sparse or too noisy to support robust learning (though part of the noise may be due to imperfect operationalization). In contr...