3 papers
eess.AS2026
Sylber 2.0: A Universal Syllable Embedding
Cheol Jun Cho, Nicholas Lee, Alan W Black +1
Scaling spoken language modeling requires speech tokens that are both efficient and universal. Recent work has proposed syllables as promising speech tokens at low temporal resolut…
cs.LG2026
Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
Immanuel Abdi, Akshat Gupta, Micah Mok +3
One of the biggest missing capabilities in current AI systems is the ability to learn continuously after deployment. Implementing such continually learning systems have several cha…
cs.CL2025
Scaling Spoken Language Models with Syllabic Speech Tokenization
Nicholas Lee, Cheol Jun Cho, Alan W Black +1
Spoken language models (SLMs) typically discretize speech into high-frame-rate tokens extracted from SSL speech models. As the most successful LMs are based on the Transformer arch…