116 citations · 808 across the 43 of their papers we have counts for
5 papers · 1 filter
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…
On Addressing Practical Challenges for RNN-Transducer
Rui Zhao, Jian Xue, Jinyu Li +3
In this paper, several works are proposed to address practical challenges for deploying RNN Transducer (RNN-T) based speech recognition system. These challenges are adapting a well…
Streaming Multi-talker Speech Recognition with Joint Speaker Identification
Liang Lu, Naoyuki Kanda, Jinyu Li +1
In multi-talker scenarios such as meetings and conversations, speech processing systems are usually required to transcribe the audio as well as identify the speakers for downstream…
Internal Language Model Training for Domain-Adaptive End-to-End Speech Recognition
Zhong Meng, Naoyuki Kanda, Yashesh Gaur +6
The efficacy of external language model (LM) integration with existing end-to-end (E2E) automatic speech recognition (ASR) systems can be improved significantly using the internal…