5 papers
Comparison of sEMG Encoding Accuracy Across Speech Modes Using Articulatory and Phoneme Features
Chenqian Le, Ruisi Li, Beatrice Fumagalli +6
We test whether Speech Articulatory Coding (SPARC) features can linearly predict surface electromyography (sEMG) envelopes across aloud, mimed, and subvocal speech in twenty-four s…
AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking
Xilin Jiang, Qiaolin Wang, Junkai Wu +30
Internet audio-visual clips convey meaning through time-varying sound and motion, which extend beyond what text alone can represent. To examine whether AI models can understand suc…
Machine Learning-Based Prediction of Speech Arrest During Direct Cortical Stimulation Mapping
Nikasadat Emami, Amirhossein Khalilian-Gourtani, Jianghao Qian +4
Identifying cortical regions critical for speech is essential for safe brain surgery in or near language areas. While Electrical Stimulation Mapping (ESM) remains the clinical gold…
A Scalable Pipeline for Estimating Verb Frame Frequencies Using Large Language Models
Adam M. Morgan, Adeen Flinker
We present an automated pipeline for estimating Verb Frame Frequencies (VFFs), the frequency with which a verb appears in particular syntactic frames. VFFs provide a powerful windo…
AAD-LLM: Neural Attention-Driven Auditory Scene Understanding
Xilin Jiang, Sukru Samet Dindar, Vishal Choudhari +6
Auditory foundation models, including auditory large language models (LLMs), process all sound inputs equally, independent of listener perception. However, human auditory perceptio…