133 citations · 138 across the 2 of their papers we have counts for
8 papers
Align-Refine: Non-Autoregressive Speech Recognition via Iterative Realignment
Ethan A. Chi, Julian Salazar, Katrin Kirchhoff
Non-autoregressive models greatly improve decoding speed over typical sequence-to-sequence models, but suffer from degraded performance. Infilling and iterative refinement models m…
Unsupervised Bitext Mining and Translation via Self-trained Contextual Embeddings
Phillip Keung, Julian Salazar, Yichao Lu +1
We describe an unsupervised method to create pseudo-parallel corpora for machine translation (MT) from unaligned text. We use multilingual BERT to create source and target sentence…
Don't Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings
Phillip Keung, Yichao Lu, Julian Salazar +1
Multilingual contextual embeddings have demonstrated state-of-the-art performance in zero-shot cross-lingual transfer learning, where multilingual BERT is fine-tuned on one source…
Attentional Speech Recognition Models Misbehave on Out-of-domain Utterances
Phillip Keung, Wei Niu, Yichao Lu +2
We discuss the problem of echographic transcription in autoregressive sequence-to-sequence attentional architectures for automatic speech recognition, where a model produces very l…
Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
Shaoshi Ling, Yuzong Liu, Julian Salazar +1
We propose a novel approach to semi-supervised automatic speech recognition (ASR). We first exploit a large amount of unlabeled audio data via representation learning, where we rec…
Masked Language Model Scoring
Julian Salazar, Davis Liang, Toan Q. Nguyen +1
Pretrained masked language models (MLMs) require finetuning for most NLP tasks. Instead, we evaluate MLMs out of the box via their pseudo-log-likelihood scores (PLLs), which are co…