3 papers
eess.AS2026
Contextual Biasing for ASR in Speech LLM with Common Word Cues and Bias Word Position Prediction
Sashi Novitasari, Takashi Fukuda, Kurata Gakuto +1
Speech-aware LLMs (SLLMs) have recently achieved state-of-the-art ASR performance; however, they still fail to accurately transcribe bias words that appear rarely or never in the t…
eess.AS2026
Self-Speculative Decoding for LLM-based ASR with CTC Encoder Drafts
George Saon, Samuel Thomas, Takashi Fukuda +3
We propose self-speculative decoding for speech-aware LLMs by using the CTC encoder as a draft model to accelerate auto-regressive (AR) inference and improve ASR accuracy. Our thre…
eess.AS2025
Granite-speech: open-source speech-aware LLMs with strong English ASR capabilities
George Saon, Avihu Dekel, Alexander Brooks +21
Granite-speech LLMs are compact and efficient speech language models specifically designed for English ASR and automatic speech translation (AST). The models were trained by modali…