A constructivist approach to infants' vowel acquisition through mother–infant interaction

Yoshikawa, Yuichiro; Asada, Minoru; Hosoda, Koh; Koga, Junpei

doi:10.1080/09540090310001655075

Cited by 91 publications

(48 citation statements)

References 8 publications

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“…In other words, the regions of sounds that the caregiver and the robot can generate are usually different from each other or do not even overlap with each other. Nevertheless, humans can map the sounds of the robot to their own corresponding vowels [7]. In contrast, it is usually not trivial for the designers to provide their robots with an accurate mapping between these two regions of sounds.…”

Section: Assumptions and Basic Concepts In Unconscious Anchoringmentioning

confidence: 99%

“…This is often referred to as the source-filter theory of speech production [12] and has been implemented in previous studies [7], [6]. To model the process of vowel convergence in mother-infant interaction, we improved the vocal robot used in a previous study [7] such that the sound source was replaced by an air . Figure 5 shows the new vocal robot.…”

Section: A Vocal Robotmentioning

confidence: 99%

“…[5], [6]) is one approach to directly attack the problem of imitation between dissimilar bodies. Using such a vocal robot, Yoshikawa et al [7] proposed a mother-infant interaction model for infant vowel acquisition based on observations in developmental psychology. Inspired by the findings that maternal imitation effectively reinforces infant vocalization [8] and that its speech-like cooing tends to invoke utterances by its mother [9], they suggested that maternal imitation (i.e., imitation of the robot's utterances by the caregiver) using adult phonemes plays an important role in phoneme acquisition, namely instructing the matching between its articulations and the corresponding caregiver's utterances.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Finding the Correspondence of Caregiver's Vowel Categories Based on Unconscious Anchoring in Maternal Imitation

Miura

Yoshikawa²,

Asada

2007

RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication

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Abstract-Due to differences in body structure between robots and humans, it is a formidable task for robots to show behaviors that correspond to human behaviors. As a simple case of this correspondence problem, this paper presents a robot that learns to vocalize vowels through interaction with its caregiver. Inspired by the findings in developmental psychology, we focus on the role of maternal imitation (i.e., imitation of a robot voice by a caregiver), which could play a role in guiding the correspondence of sounds. Furthermore, we suppose that it causes unconscious anchoring in which the imitated voice by the caregiver is approaching to one of his/her own vowels without his/her intension, and thereby works for guiding robot's utterances to be more vowel-like. We propose a method for vowel learning with an imitative caregiver under the assumption that the robot knows the desired categories of caregiver's vowels and the rough estimate of mapping between the region of sounds that the caregiver can generate and the region that the robot can generate. Through experiments with a Japanese imitative caregiver, we show that a robot succeeds in acquiring more vowel-like utterances than would be possible without such a caregiver, even when the robot is provided different mapping functions.

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Section: Assumptions and Basic Concepts In Unconscious Anchoringmentioning

confidence: 99%

Section: A Vocal Robotmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Finding the Correspondence of Caregiver's Vowel Categories Based on Unconscious Anchoring in Maternal Imitation

Miura

Yoshikawa²,

Asada

2007

RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication

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show abstract

“…Yoshikawa et al [8] constructively showed that imitation by the caregiver in response to infant's vocalization with vowels plays an important role in vowel acquisition. Considering well-known "perceptual magnet effect" [9] by which person's perception of phonemes is biased to his/her own category, Miura et al [1] showed that the utterance of baby robot could be leaded to clear vowel sound through the mutual imitation with its caregiver.…”

Section: Introductionmentioning

confidence: 99%

Realizing being imitated: Vowel mapping with clearer articulation

Miura¹,

Yoshikawa

Asada³

2008

2008 7th IEEE International Conference on Development and Learning

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Abstract-The previous approach to vowel imitation learning between a caregiver and an infant (robot) [1] has assumed that the robot can segment the caregiver's utterance into its phoneme category, where the caregiver always imitates the robot utterance. However, in real situations, the caregiver does not always imitate the robot utterance, nor the robot does have the phoneme category (no segmentation capability). This paper presents a method to solve these issues, a weakly-supervised learning along with auto-regulation, that is active selection of action and data with underdeveloped classifier. To cope with notalways imitation problem, a weakly-supervised learning method is applied that is capable to handle incompletely segmented samples (not perfectly imitated voices). Further, the regulation classifier of the imitated voices is recursively applied in order to select good vocal primitives and to segment caregiver's imitated voices that improve the performance of the classifier itself. The simulation results are shown and the future issues are given.

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“…A cross modal map is proposed as the learning structure based on the idea that the invariance in multisensory data represents the body. Concerning the construction of a mapping between different bodies, we address the problem of acquiring common vowels with the caregiver who has different articulation parameters from the robot [5]. We propose a model of interaction that guides a robot to acquire articulation to vocalize.…”

Section: Introductionmentioning

confidence: 99%

Towards Imitation Learning from a Viewpoint of an Internal Observer

Yoshikawa

Asada

Hosoda

2004

Embodied Artificial Intelligence

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Abstract. How an internal observer, that is not given any a priori knowledge or interpretation of what its sensors receives, learn to imitate seems a formidable issue from a viewpoint of a constructivist approach towards both establishing the design principle for an intelligent robot and understanding human intelligence. This paper argue two issues towards imitation by an internal observer: one concerns how to construct the self body representation of the robot with vision and proprioception and the other concerns how to construct a mapping of vocalization between agents with different articulation systems. Preliminary results with real robots are given.

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A constructivist approach to infants' vowel acquisition through mother–infant interaction

Cited by 91 publications

References 8 publications

Finding the Correspondence of Caregiver's Vowel Categories Based on Unconscious Anchoring in Maternal Imitation

Finding the Correspondence of Caregiver's Vowel Categories Based on Unconscious Anchoring in Maternal Imitation

Realizing being imitated: Vowel mapping with clearer articulation

Towards Imitation Learning from a Viewpoint of an Internal Observer

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