activity
20232026
collaborators

7 papers

cs.SD2026

Compressing Streaming Neural Audio Encoders via Latent-Space Distillation

Prasanth Yadla, Mohammad Samragh, Dongseong Hwang +7

System-wide Dictation on Apple devices runs entirely on-device, and the speech it transcribes reaches the foundation model through a tokenizer: an encoder that maps short windows o…

eess.AS2024

Contextualization of ASR with LLM using phonetic retrieval-based augmentation

Zhihong Lei, Xingyu Na, Mingbin Xu +5

Large language models (LLMs) have shown superb capability of modeling multimodal signals including audio and text, allowing the model to generate spoken or textual response given a…

cs.LG2024

Focused Discriminative Training For Streaming CTC-Trained Automatic Speech Recognition Models

Adnan Haider, Xingyu Na, Erik McDermott +3

This paper introduces a novel training framework called Focused Discriminative Training (FDT) to further improve streaming word-piece end-to-end (E2E) automatic speech recognition…

eess.AS2024

Enhancing CTC-based speech recognition with diverse modeling units

Shiyi Han, Zhihong Lei, Mingbin Xu +2

In recent years, the evolution of end-to-end (E2E) automatic speech recognition (ASR) models has been remarkable, largely due to advances in deep learning architectures like transf…

cs.LG2023

Conformer-Based Speech Recognition On Extreme Edge-Computing Devices

Mingbin Xu, Alex Jin, Sicheng Wang +8

With increasingly more powerful compute capabilities and resources in today's devices, traditionally compute-intensive automatic speech recognition (ASR) has been moving from the c…

cs.LG2023

Personalization of CTC-based End-to-End Speech Recognition Using Pronunciation-Driven Subword Tokenization

Zhihong Lei, Ernest Pusateri, Shiyi Han +8

Recent advances in deep learning and automatic speech recognition have improved the accuracy of end-to-end speech recognition systems, but recognition of personal content such as c…

cs.SD2023

Acoustic Model Fusion for End-to-end Speech Recognition

Zhihong Lei, Mingbin Xu, Shiyi Han +8

Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted the accuracy to a new level. The E2E systems implic…