most citedGranite-speech: open-source speech-aware LLMs with strong English ASR capabilities

1 citations · 1 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL2026

Preference-Aware Pareto Steering for Multi-Task Speech LLMs

Liuyuan Jiang, Vishal Sunder, Samuel Thomas +4

Speech large language models (LLMs) perform multiple tasks, including automatic speech recognition (ASR), timestamp prediction (TS), and speech translation (ST). Joint training of…

cs.CL2026

Design of the IBM Granite 5.0 TurboCTC ASR Model

Brian Kingsbury, George Saon, Masayuki Suzuki +5

We describe the architecture, training methodology and inference speedups of Granite 5.0 Turbo CTC, a 470 million parameter encoder-only model with an excellent speed-accuracy trad…

eess.AS2026

CHILDES-Aligned: A Curated Children's Speech Dataset via Multi-Model Timestamp Ensembling

Haolong Zheng, Yuanzhuo Hu, Xinyu Liang +7

CHILDES is a large-scale child speech corpus containing long-form recordings of naturalistic child-adult interactions, making it a valuable resource for studying child speech and l…

eess.AS2026

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…

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.AS2026

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…

eess.AS2025★ 1 cited

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…

cs.SD2025

A Non-autoregressive Model for Joint STT and TTS

Vishal Sunder, Brian Kingsbury, George Saon +5

In this paper, we take a step towards jointly modeling automatic speech recognition (STT) and speech synthesis (TTS) in a fully non-autoregressive way. We develop a novel multimoda…