arXiv:2607. 06831v1 Announce Type: cross Abstract: Speech-to-text alignment means finding the temporal boundaries of each word in the audio.
By Albert Zeyer, Ralf Schl\"uter, Hermann Ney
arXiv:2604.06487v2 Announce Type: replace
Abstract: Conventional end-to-end automatic speech recognition (ASR) systems rely on paired speech-text data for domain adaptation. Recent LLM-based ASR arch...
By Thibault Ba\~neras-Roux, Sergio Burdisso, Esa\'u Villatoro-Tello, Dairazalia S\'anchez-Cort\'es, Shiran Liu, Severin Baroudi, Shashi Kumar, Hasindri Watawana, Manjunath K E, Kadri Hacioglu, Petr Motlicek, Andreas Stolcke
arXiv:2609.17981v1 Announce Type: cross
Abstract: Speech Large Language Models (Speech-LLMs), typically built from a pre-trained speech encoder, a modality projector, and an LLM fine-tuned with Low-R...
By Mohan Shi, Zilai Wang, Natarajan Balaji Shankar, Kaiyuan Zhang, Eray Eren, Abeer Alwan
arXiv:2602.19574v2 Announce Type: replace-cross
Abstract: Large-language-model (LLM)-based text-to-speech (TTS) systems can generate natural speech, but most are not designed for low-latency dual-str...
By Hanwen Liu, Saierdaer Yusuyin, Hao Huang, Zhijian Ou
The paper introduces an Adaptive Duration Model designed to predict phoneme-level duration distributions directly from text, improving alignment in text-to-speech systems. It outperforms existing baseline models in precision and adaptability to varying conditions, enhancing phoneme-level alignment accuracy. The model also strengthens zero‑shot TTS performance by reducing sensitivity to mismatches between prompt and input audio.
By Junjie Cao
arXiv:2601.20900v4 Announce Type: replace-cross
Abstract: Adapting large language model (LLM)-based automatic speech recognition (ASR) systems to new domains using text-only data is a significant yet...
By Andr\'es Carofilis, Sergio Burdisso, Esa\'u Villatoro-Tello, Shashi Kumar, Kadri Hacioglu, Srikanth Madikeri, Pradeep Rangappa, Manjunath K E, Petr Motlicek, Shankar Venkatesan, Andreas Stolcke