Apoorv Vyas | DeepAI

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∙ 06/23/2023

Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale

Large-scale generative models such as GPT and DALL-E have revolutionized...

0 Matthew Le, et al. ∙

∙ 05/22/2023

Scaling Speech Technology to 1,000+ Languages

Expanding the language coverage of speech technology has the potential t...

0 Vineel Pratap, et al. ∙

∙ 04/25/2022

On-demand compute reduction with stochastic wav2vec 2.0

Squeeze and Efficient Wav2vec (SEW) is a recently proposed architecture ...

0 Apoorv Vyas, et al. ∙

∙ 04/06/2021

Comparing CTC and LFMMI for out-of-domain adaptation of wav2vec 2.0 acoustic model

In this work, we investigate if the wav2vec 2.0 self-supervised pretrain...

0 Apoorv Vyas, et al. ∙

∙ 12/28/2020

Lattice-Free MMI Adaptation Of Self-Supervised Pretrained Acoustic Models

In this work, we propose lattice-free MMI (LFMMI) for supervised adaptat...

0 Apoorv Vyas, et al. ∙

∙ 10/07/2020

Pkwrap: a PyTorch Package for LF-MMI Training of Acoustic Models

We present a simple wrapper that is useful to train acoustic models in P...

0 Srikanth Madikeri, et al. ∙

∙ 07/09/2020

Fast Transformers with Clustered Attention

Transformers have been proven a successful model for a variety of tasks ...

34 Apoorv Vyas, et al. ∙

∙ 06/29/2020

Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

Transformers achieve remarkable performance in several tasks but due to ...

35 Angelos Katharopoulos, et al. ∙

∙ 09/04/2018

Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers

As deep learning methods form a critical part in commercially important ...

0 Apoorv Vyas, et al. ∙

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