8 papers
In-Sync: Adaptation of Speech Aware Large Language Models for ASR with Word Level Timestamp Predictions
Xulin Fan, Vishal Sunder, Samuel Thomas +3
Recent advances in speech-aware language models have coupled strong acoustic encoders with large language models, enabling systems that move beyond transcription to produce richer…
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…
Speaker Attributed Automatic Speech Recognition Using Speech Aware LLMS
Hagai Aronowitz, Zvi Kons, Avihu Dekel +2
Speaker-Attributed Automatic Speech Recognition (SAA) enhances traditional ASR systems by incorporating relative speaker identity tags directly into the transcript (e.g., [Speaker…
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…
NLE: Non-autoregressive LLM-based ASR by Transcript Editing
Avihu Dekel, Samuel Thomas, Takashi Fukada +1
While autoregressive (AR) LLM-based ASR systems achieve strong accuracy, their sequential decoding limits parallelism and incurs high latency. We propose NLE, a non-autoregressive…
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…