Browsing by Author "Cristia, A"

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Open Access
Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech
(Speech Communication, 2019-10-01) Räsänen, O; Seshadri, S; Karadayi, J; Riebling, E; Bunce, J; Cristia, A; Metze, F; Casillas, M; Rosemberg, C; Bergelson, E; Soderstrom, M
© 2019 The Authors 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.
Open Access
Quantifying Sources of Variability in Infancy Research Using the Infant-Directed-Speech Preference
(Advances in Methods and Practices in Psychological Science, 2020-03) Frank, MC; Alcock, KJ; Arias-Trejo, N; Aschersleben, G; Baldwin, D; Barbu, S; Bergelson, E; Bergmann, C; Black, AK; Blything, R; Böhland, MP; Bolitho, P; Borovsky, A; Brady, SM; Braun, B; Brown, A; Byers-Heinlein, K; Campbell, LE; Cashon, C; Choi, M; Christodoulou, J; Cirelli, LK; Conte, S; Cordes, S; Cox, C; Cristia, A; Cusack, R; Davies, C; de Klerk, M; Delle Luche, C; de Ruiter, L; Dinakar, D; Dixon, KC; Durier, V; Durrant, S; Fennell, C; Ferguson, B; Ferry, A; Fikkert, P; Flanagan, T; Floccia, C; Foley, M; Fritzsche, T; Frost, RLA; Gampe, A; Gervain, J; Gonzalez-Gomez, N; Gupta, A; Hahn, LE; Hamlin, JK; Hannon, EE; Havron, N; Hay, J; Hernik, M; Höhle, B; Houston, DM; Howard, LH; Ishikawa, M; Itakura, S; Jackson, I; Jakobsen, KV; Jarto, M; Johnson, SP; Junge, C; Karadag, D; Kartushina, N; Kellier, DJ; Keren-Portnoy, T; Klassen, K; Kline, M; Ko, ES; Kominsky, JF; Kosie, JE; Kragness, HE; Krieger, AAR; Krieger, F; Lany, J; Lazo, RJ; Lee, M; Leservoisier, C; Levelt, C; Lew-Williams, C; Lippold, M; Liszkowski, U; Liu, L; Luke, SG; Lundwall, RA; Cassia, VM; Mani, N; Marino, C; Martin, A; Mastroberardino, M; Mateu, V; Mayor, J; Menn, K; Michel, C; Moriguchi, Y; Morris, B; Nave, KM; Nazzi, T
Psychological scientists have become increasingly concerned with issues related to methodology and replicability, and infancy researchers in particular face specific challenges related to replicability: For example, high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations. Addressing these concerns, we report on a large-scale, multisite study aimed at (a) assessing the overall replicability of a single theoretically important phenomenon and (b) examining methodological, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an adult in North American English were created using seminaturalistic laboratory-based audio recordings. Infants’ relative preference for IDS and ADS was assessed across 67 laboratories in North America, Europe, Australia, and Asia using the three common methods for measuring infants’ discrimination (head-turn preference, central fixation, and eye tracking). The overall meta-analytic effect size (Cohen’s d) was 0.35, 95% confidence interval = [0.29, 0.42], which was reliably above zero but smaller than the meta-analytic mean computed from previous literature (0.67). The IDS preference was significantly stronger in older children, in those children for whom the stimuli matched their native language and dialect, and in data from labs using the head-turn preference procedure. Together, these findings replicate the IDS preference but suggest that its magnitude is modulated by development, native-language experience, and testing procedure.