A. Stolcke

Context Projector: Complementary Keyword and Dialogue Context Embeddings for LLM-based ASR

Closing the Speech-Text Gap with Limited Audio for Effective Domain Adaptation in LLM-Based ASR

MB using only 10% of the target-domain speech achieves word error rates comparable to, or better than, conventional ASR fine-tuning with the full dataset, indicating that small amounts of speech provide a strong modality-alignment signal.

Reading Emotions in the Token Space: Discriminative Adaptation of SpeechLLMs for Emotion Recognition

A discriminative adaptation that reads the final prompt token's hidden state through a classification head, producing a label in one forward pass without modifying the backbone, gives a controlled comparison of generative and discriminative inference in an otherwise identical speechLLM.

Less can be More: What Aspects of Speech Drive End-of-Turn Detection

These findings suggest that turn-taking is primarily conveyed through intonation and silence patterns rather than semantic completeness, enabling faster and more reliable systems without expensive text inference.

LLMs Get Smarter from Targeted Synthetic Multilingual Data

HOTFIXR: Hardness Optimized Training data For Improving X-Lingual Reasoning is a data generation framework that uses models to probe and learn a student model's multilingual weaknesses, and generates data to mitigate them that can improve multilingual performance.

When Synthetic Speech Is All You Have: Better Call GRPO

This work shows that Group Relative Policy Optimization (GRPO) extracts far more from the same synthetic speech than SFT, and traces the gain to behavior rather than representation: GRPO reduces insertion errors by improving stopping calibration and speech-to-text alignment by better anchoring attention to audio, leavi...