Publications

Abstract

- * indicates joint first authorship - Abstract: A range of demographic variables influence how much speech young children hear. However, because studies have used vastly different sampling methods, quantitative comparison of interlocking demographic effects has been nearly impossible, across or within studies. We harnessed a unique collection of existing naturalistic, day-long recordings from 61 homes across four North American cities to examine language input as a function of age, gender, and maternal education. We analyzed adult speech heard by 3- to 20-month-olds who wore audio recorders for an entire day. We annotated speaker gender and speech register (child-directed or adult-directed) for 10,861 utterances from female and male adults in these recordings. Examining age, gender, and maternal education collectively in this ecologically-valid dataset, we find several key results. First, the speaker gender imbalance in the input is striking: children heard 2--3x more speech from females than males. Second, children in higher-maternal-education homes heard more child-directed speech than those in lower-maternal education homes. Finally, our analyses revealed a previously unreported effect: the proportion of child-directed speech in the input increases with age, due to a decrease in adult-directed speech with age. This large-scale analysis is an important step forward in collectively examining demographic variables that influence early development, made possible by pooled, comparable, day-long recordings of children's language environments. The audio recordings, annotations, and annotation software are readily available for re-use and re-analysis by other researchers.

Abstract

Recent years have seen rapid technological development of devices that can record communicative behavior as participants go about daily life. This paper is intended as an end-to-end methodological guidebook for potential users of these technologies, including researchers who want to study children’s or adults’ communicative behavior in everyday contexts. We explain how long-format speech environment (LFSE) recordings provide a unique view on language use and how they can be used to complement other measures at the individual and group level. We aim to help potential users of these technologies make informed decisions regarding research design, hardware, software, and archiving. We also provide information regarding ethics and implementation, issues that are difficult to navigate for those new to this technology, and on which little or no resources are available. This guidebook offers a concise summary of information for new users and points to sources of more detailed information for more advanced users. Links to discussion groups and community-augmented databases are also provided to help readers stay up-to-date on the latest developments.

Abstract

Odor naming is enhanced in communities where communication about odors is a central part of daily life (e.g., wine experts, flavorists, and some hunter‐gatherer groups). In this study, we investigated how expert knowledge and daily experience affect the ability to name odors in a group of experts that has not previously been investigated in this context—Iranian herbalists; also called attars—as well as cooks and laypeople. We assessed naming accuracy and consistency for 16 herb and spice odors, collected judgments of odor perception, and evaluated participants' odor meta‐awareness. Participants' responses were overall more consistent and accurate for more frequent and familiar odors. Moreover, attars were more accurate than both cooks and laypeople at naming odors, although cooks did not perform significantly better than laypeople. Attars' perceptual ratings of odors and their overall odor meta‐awareness suggest they are also more attuned to odors than the other two groups. To conclude, Iranian attars—but not cooks—are better odor namers than laypeople. They also have greater meta‐awareness and differential perceptual responses to odors. These findings further highlight the critical role that expertise and type of experience have on olfactory functions.

Abstract

Automatic word count estimation (WCE) from audio recordings can be used to quantify the amount of verbal communication in a recording environment. One key application of WCE is to measure language input heard by infants and toddlers in their natural environments, as captured by daylong recordings from microphones worn by the infants. Although WCE is nearly trivial for high-quality signals in high-resource languages, daylong recordings are substantially more challenging due to the unconstrained acoustic environments and the presence of near- and far-field speech. Moreover, many use cases of interest involve languages for which reliable ASR systems or even well-defined lexicons are not available. A good WCE system should also perform similarly for low- and high-resource languages in order to enable unbiased comparisons across different cultures and environments. Unfortunately, the current state-of-the-art solution, the LENA system, is based on proprietary software and has only been optimized for American English, limiting its applicability. In this paper, we build on existing work on WCE and present the steps we have taken towards a freely available system for WCE that can be adapted to different languages or dialects with a limited amount of orthographically transcribed speech data. Our system is based on language-independent syllabification of speech, followed by a language-dependent mapping from syllable counts (and a number of other acoustic features) to the corresponding word count estimates. We evaluate our system on samples from daylong infant recordings from six different corpora consisting of several languages and socioeconomic environments, all manually annotated with the same protocol to allow direct comparison. We compare a number of alternative techniques for the two key components in our system: speech activity detection and automatic syllabification of speech. As a result, we show that our system can reach relatively consistent WCE accuracy across multiple corpora and languages (with some limitations). In addition, the system outperforms LENA on three of the four corpora consisting of different varieties of English. We also demonstrate how an automatic neural network-based syllabifier, when trained on multiple languages, generalizes well to novel languages beyond the training data, outperforming two previously proposed unsupervised syllabifiers as a feature extractor for WCE.

Abstract

Understanding how communicative goals impact and drive the learning process has been a long-standing issue in the field of language acquisition. Recent years have seen renewed interest in the social and pragmatic aspects of language learning: the way interaction shapes what and how children learn. In this volume, we bring together researchers working on interaction in different domains to present a cohesive overview of ongoing interactional research. The studies address the diversity of the environments children learn in; the role of para-linguistic information; the pragmatic forces driving language learning; and the way communicative pressures impact language use and change. Using observational, empirical and computational findings, this volume highlights the effect of interpersonal communication on what children hear and what they learn. This anthology is inspired by and dedicated to Prof. Eve V. Clark – a pioneer in all matters related to language acquisition – and a major force in establishing interaction and communication as crucial aspects of language learning.

Abstract

A key part of learning to speak with others is figuring out when to start talking and how to hold the floor in conversation. For young children, the challenge of planning a linguistic response can slow down their response latencies, making misunderstanding, repair, and loss of the floor more likely. Like adults, children can mitigate their delays by using fillers (e.g., uh and um) at the start of their turns. In this chapter I analyze the onset and development of fillers in five children’s spontaneous speech from ages 1;6–3;6. My findings suggest that children start using fillers by 2;0, and use them to effectively mitigate delay in making a response.

Abstract

Conversation is a structured, joint action for which children need to learn a specialized set skills and conventions. Because conversation is a primary source of linguistic input, we can better grasp how children become active agents in their own linguistic development by studying their acquisition of conversational skills. In this chapter I review research on children’s turn-taking. This fundamental skill of human interaction allows children to gain feedback, make clarifications, and test hypotheses at every stage of development. I broadly review children’s conversational experiences, the types of turn-based contingency they must acquire, how they ask and answer questions, and when they manage to make timely responses

Abstract

When we think of children acquiring language, we often think of their acquisition of linguistic structure as separate from their acquisition of knowledge about the world. But it is clear that in the process of learning about language, children consult what they know about the world; and that in learning about the world, children use linguistic cues to discover how items are related to one another. This interaction between the acquisition of linguistic structure and the acquisition of category structure is especially clear in word learning.