30 citations · 65 across the 9 of their papers we have counts for
9 papers
Clustering and Mining Accented Speech for Inclusive and Fair Speech Recognition
Jaeyoung Kim, Han Lu, Soheil Khorram +3
Modern automatic speech recognition (ASR) systems are typically trained on more than tens of thousands hours of speech data, which is one of the main factors for their great succes…
Augmenting Transformer-Transducer Based Speaker Change Detection With Token-Level Training Loss
Guanlong Zhao, Quan Wang, Han Lu +2
In this work we propose a novel token-based training strategy that improves Transformer-Transducer (T-T) based speaker change detection (SCD) performance. The conventional T-T base…
Contrastive Siamese Network for Semi-supervised Speech Recognition
Soheil Khorram, Jaeyoung Kim, Anshuman Tripathi +3
This paper introduces contrastive siamese (c-siam) network, an architecture for leveraging unlabeled acoustic data in speech recognition. c-siam is the first network that extracts…
Turn-to-Diarize: Online Speaker Diarization Constrained by Transformer Transducer Speaker Turn Detection
Wei Xia, Han Lu, Quan Wang +4
In this paper, we present a novel speaker diarization system for streaming on-device applications. In this system, we use a transformer transducer to detect the speaker turns, repr…
Reducing Streaming ASR Model Delay with Self Alignment
Jaeyoung Kim, Han Lu, Anshuman Tripathi +2
Reducing prediction delay for streaming end-to-end ASR models with minimal performance regression is a challenging problem. Constrained alignment is a well-known existing approach…
Transformer Transducer: One Model Unifying Streaming and Non-streaming Speech Recognition
Anshuman Tripathi, Jaeyoung Kim, Qian Zhang +2
In this paper we present a Transformer-Transducer model architecture and a training technique to unify streaming and non-streaming speech recognition models into one model. The mod…