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!
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"
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"
https://t.co/yAo4WlVnlt
🧵1/n
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
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
https://t.co/B4NQKmUbdL
🧵1/x
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
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..."
https://t.co/JW0lXyVYlp
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
Happy publication day to Robert Fromont and co-authors: Maximizing accuracy of forced alignment for spontaneous child speech https://t.co/mZxyIqFdbh 🧵1/n
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