A preliminary study on the adaptation of Whisper for Automatic Speech Recognition in Baniwa, an indigenous Arawakan language spoken in Brazil, Colombia, and Venezuela, demonstrating that multilingual foundation models can be successfully adapted to extremely low-resource indigenous languages.
Abstract
Automatic Speech Recognition (ASR) technologies have achieved remarkable performance in recent years through the use of large multilingual foundation models. However, most advances remain concentrated on high-resource languages, while indigenous languages continue to suffer from a lack of speech resources and language technologies. This work presents a preliminary study on the adaptation of Whisper for Automatic Speech Recognition in Baniwa, an indigenous Arawakan language spoken in Brazil, Colombia, and Venezuela. The experiments were conducted using a corpus of 1,373 manually transcribed recordings obtained from a linguistic documentation project. The corpus contains approximately 0.54 hours of speech and consists primarily of isolated words and short elicited utterances. The Whisper Small model was fine-tuned using supervised learning and evaluated using Word Error Rate (WER) and Character Error Rate (CER). The best model achieved a WER of 37.5% and a CER of 7.45%, demonstrating that multilingual foundation models can be successfully adapted to extremely low-resource indigenous languages. The results establish an initial baseline for Baniwa Automatic Speech Recognition and provide a foundation for future research involving larger datasets, language-specific adaptation strategies, and post-processing techniques.
LifeSciBench is introduced, a benchmark of 750 expert-authored tasks designed to evaluate whether language models can handle realistic life science research work, with each constituent task paired with a human expert-written rubric.
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A rapidly advancing precision-therapy pipeline-including antisense oligonucleotides to upregulate the intact allele, AAV-based gene replacement, CRISPR-mediated transcriptional activation, epigenetic modulators, and rational pathway-targeted small molecules-offers realistic prospects for disease modification.
Autistic children experience disproportionately high rates of anxiety, yet common interventions such as cognitive behavioural therapy and traditional mindfulness practices may be less effective due to their cognitive and abstract demands. Yoga nidra, a form of guided meditation using concrete visualisations and breath awareness, may offer a more accessible alternative. This mixed methods study evaluated the feasibility and pilot efficacy of a co-designed six-week online yoga nidra intervention targeting anxiety in autistic children aged 8-14 years. Neurophysiological and psychological data were collected from 13 participants using parent- and self-reported measures of anxiety (ASC-ASD), intolerance of uncertainty (IUSC), and emotion dysregulation (EDI), alongside heart rate variability (HRV). Notably, the cohort included a minimally speaking child, which demonstrates the potential for the intervention to extend to autistic children with language support needs, a group who are often underrepresented in similar research. Results indicated no statistically significant changes in anxiety over time; however, medium effect sizes were observed in self- (Hedge's g = 0.55) and parent-reported anxiety (Hedge's g = 0.45), with three participants moving from clinically significant to non-significant anxiety levels post-intervention. Additionally, intolerance of uncertainty and emotion dysregulation demonstrated small to medium effect size reductions (IUSC, Hedge's g = 0.50; EDI-Reactivity, Hedge's g = 0.55; EDI-Dysphoria, Hedge's g = 0.25), suggesting potential benefits of yoga nidra in these areas. Greater attendance was significantly associated with self-reported reductions in anxiety (ASC-ASD-SR, r = .757, p < .05), but not the other outcome measures. Unexpectedly, HRV outcomes indicated reduced autonomic functioning post-intervention. Additionally, qualitative data from semi-structured interviews with three child participants and their mothers from the study were analysed using reflexive thematic analysis, revealing five key themes of their experience: Thinking About the Body is Hard; We Want More; Homework Sucks; Making Mindfulness Concrete; and On-Screen and At Home is Convenient. While the online format was appreciated for its accessibility, challenges with adherence and scheduling highlighted the need for more flexible delivery models. This study advances upon prior research by being the first to develop a co-designed yoga nidra intervention specifically for autistic children. Findings support the feasibility of yoga nidra as a complementary intervention for autistic children and suggest directions for future research, including larger trials and further co-design with the autistic community.
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