3 papers
cs.SD2022
Adding Connectionist Temporal Summarization into Conformer to Improve Its Decoder Efficiency For Speech Recognition
Nick J. C. Wang, Zongfeng Quan, Shaojun Wang +1
The Conformer model is an excellent architecture for speech recognition modeling that effectively utilizes the hybrid losses of connectionist temporal classification (CTC) and atte…
cs.CL2022
A Study of Different Ways to Use The Conformer Model For Spoken Language Understanding
Nick J. C. Wang, Shaojun Wang, Jing Xiao
SLU combines ASR and NLU capabilities to accomplish speech-to-intent understanding. In this paper, we compare different ways to combine ASR and NLU, in particular using a single Co…
cs.CL2022
Three-Module Modeling For End-to-End Spoken Language Understanding Using Pre-trained DNN-HMM-Based Acoustic-Phonetic Model
Nick J. C. Wang, Lu Wang, Yandan Sun +2
In spoken language understanding (SLU), what the user says is converted to his/her intent. Recent work on end-to-end SLU has shown that accuracy can be improved via pre-training ap…