4 accepted papers
Continual learning (CL), or domain expansion, recently became a popular topic for automatic speech recognition (ASR) acoustic modeling because practical systems have to be updated frequently in order to work robustly on types of speech not observed during initial training. While sequential adaptatio…
Self-attention - an attention mechanism where the input and output sequence lengths are the same - has recently been successfully applied to machine translation, caption generation, and phoneme recognition. In this paper we apply a restricted self-attention mechanism (with multiple heads) to speech…
The lattice-free MMI objective (LF-MMI) has been used in supervised training of state-of-the-art neural network acoustic models for automatic speech recognition (ASR). With large amounts of unsupervised data available, extending this approach to the semi-supervised scenario is of significance. Finit…
I-vectors have proved to be the most effective features for text-independent speaker verification in recent researches. In this article a new scheme is proposed to utilize i-vectors in text-prompted speaker verification in a simple while effective manner. In order to examine this scheme empirically,…