Language Development Research

Thanks to our new followers, but we're not active on here anymore - please join us at the other place - the one where the sky is blue!

Hi everyone - We're not killing this account off just yet but like many people/organizations we're essentially transferring to the other place - see you there!

@LangDevRes @LVKremin @Concordia @Princeton It was a wonderful experience publishing with @LangDevRes ! So glad we have this platinum #OpenAccess journal in our field! Two thumbs up 👍 👍

Conclusion "It is not scientifically sound to tell parents that code-switching is ‘good’ or ‘bad’... future experiments...[should] carefully document young bilinguals’ everyday experience with code-switching & evaluate how they process instances of typical and atypical switching"

How come? Here, the switch came at an uninformative adjective (e.g., "le bon" duck didn't help children with their task of finding the duck onscreen) so maybe that's why it didn't interfere with processing (and perhaps the switch boosted attention) 4/n

Another NEW platinum-open-access article with important real-world implications: @LVKremin, Amel Jordan, Casey Lew-Williams and @Krista_BH @Concordia @Princeton - "Bilingual children’s comprehension of code-switching at an uninformative adjective" doi.org/10.34842/zyvj-… 🧵1/n

@LingeborgSophie @Many_Babies Yes please!

@LangDevRes @Many_Babies Do you still need one?

For MB folks still here who are interested in *airquotes* other options */airquotes*, we have a few invite codes available :)

And of course, their classifier tool is freely available for colleagues too: github.com/kachergis/tCDS… 7/7

We're honoured that these researchers have chosen to publish such methodologically groundbreaking research with LDR, and thank them for supporting our platinum open access (that's no fees for anyone!) model. 6/x

Happy publication day to Janet Bang, George @kachergis Adriana Weisleder @adriweis and Virginia @V_Marchman for their groundbreaking methods paper: An automated classifier for periods of sleep and target-child-directed speech from LENA recordings doi.org/10.34842/xmrq-… 🧵1/x

Forced aligners work better on adults than children. We tried different aligner configs with HTK and MFA, thinking that using child speech in training data would be important. We were wrong, MFA with models pretrained on lots of adult speech was better than anything else!

@wavable And thanks @LangDevRes for being a cool Open Science journal! "We don't believe in locking articles behind paywalls, in charging taxpayers and universities to publish research they've already funded..." ldr.lps.library.cmu.edu

Overall the authors conclude that these tools can be very useful for working with child speech, but aren't yet at the stage where they can completely replace manual coding 6/6

And perhaps surprisingly, having LOTS of training data was more important than having training data similar to the child test data. The "winner" was trained on adult speech (just lots of it) 5/n

Happy publication day to Robert Fromont and co-authors: Maximizing accuracy of forced alignment for spontaneous child speech doi.org/10.34842/shrr-… 🧵1/n