Users can find new features and updates in this page.
Standard bug fixes and a new aesthetic design.
Translation is now more accessible.
The What is New page has been added in Open Brain AI to keep track of the changes, additions and modifications in Open Brain AI.
The lexical output has been updated with Mean Lenght of Utterance measure. The measure existed only in our offline models, now it has been added on the online platform as well.
The Documentation page has been updated to provide more information on the Language Measures, specifically what is meant by Function and Content words (after request from users).
The Phonology Scoring App, Spelling Scoring App, and IPA Transcription App now support 67 languages and varieties! Perfect for linguists, SLPs, and researchers!
The Phonology Scoring App and the Spelling Scoring App now provide additional scores for insertions, deletions, substitutions, and transpositions. These provide more detailed information on the type of errors produced in both oral and written speech.
We added a Documentation page to unify all help and support in one place. Previously, each tool had its own documentation at same page, which resulted in a more cluttered environment.
Spelling Application First development of this tool as a desktop application.
(see our about page for more)
Brain injuries resulting from stroke can affect the production of speech (Brook-shire and McNeil, 2014; Plowman et al., 2012). Studying these productions manually is an extremely cumbersome and time consuming process, as it often requires the transcription of speech signals and the extraction of information. The aim of this paper is to present THEMIS_SV a system that enables the automatic transcription of speech signals and the segmentation of vowels and consonants in Swedish. The input of the system are recordings of speech. The system processes these recordings and returns an output with three tiers: the utterance tier, the word tier, and the vowels and consonants tier (see an example output Figure 2). The automatic segmentation of speech can enable targeted acoustic measurements, such as measurements of consonant spectra, formant frequencies of vowels, fundamental frequency, pauses, speech rate, etc. and other acoustic measurements that have been known to differentiate between the different types of language disorders (see Figure 1). The method proposed here can be employed for the analysis of speech of individuals with post-stroke aphasia and other speech disorders and constitutes a promising step towards a fully automated differential diagnostic tool for language disorders.
Brookshire R. H., M. R. McNeil, Introduction to Neurogenic CommunicationDisorders-E-Book, Elsevier Health Sciences, 2014.E. Plowman, B. Hentz, C. Ellis, Post-stroke aphasia prognosis: A review of patient-related and stroke-related factors, Journal of evaluation in clinical practice 18 (2012)689–694.
Plowman E., B. Hentz, C. Ellis, Post-stroke aphasia prognosis: A review of patient-related and stroke-related factors, Journal of evaluation in clinical practice 18 (2012)689–694.