24 citations · 73 across the 14 of their papers we have counts for
14 papers
Efficient Long-Form Speech Recognition for General Speech In-Context Learning
Hao Yen, Shaoshi Ling, Guoli Ye
We propose a novel approach to end-to-end automatic speech recognition (ASR) to achieve efficient speech in-context learning (SICL) for (i) long-form speech decoding, (ii) test-tim…
Hybrid Attention-based Encoder-decoder Model for Efficient Language Model Adaptation
Shaoshi Ling, Guoli Ye, Rui Zhao +1
The attention-based encoder-decoder (AED) speech recognition model has been widely successful in recent years. However, the joint optimization of acoustic model and language model…
Adapting Large Language Model with Speech for Fully Formatted End-to-End Speech Recognition
Shaoshi Ling, Yuxuan Hu, Shuangbei Qian +5
Most end-to-end (E2E) speech recognition models are composed of encoder and decoder blocks that perform acoustic and language modeling functions. Pretrained large language models (…
Acoustic-aware Non-autoregressive Spell Correction with Mask Sample Decoding
Ruchao Fan, Guoli Ye, Yashesh Gaur +1
Masked language model (MLM) has been widely used for understanding tasks, e.g. BERT. Recently, MLM has also been used for generation tasks. The most popular one in speech is using…
Have best of both worlds: two-pass hybrid and E2E cascading framework for speech recognition
Guoli Ye, Vadim Mazalov, Jinyu Li +1
Hybrid and end-to-end (E2E) systems have their individual advantages, with different error patterns in the speech recognition results. By jointly modeling audio and text, the E2E m…
Minimum Word Error Rate Training with Language Model Fusion for End-to-End Speech Recognition
Zhong Meng, Yu Wu, Naoyuki Kanda +6
Integrating external language models (LMs) into end-to-end (E2E) models remains a challenging task for domain-adaptive speech recognition. Recently, internal language model estimat…