31 citations · 70 across the 4 of their papers we have counts for
4 papers · 1 filter
SpeakerNet: 1D Depth-wise Separable Convolutional Network for Text-Independent Speaker Recognition and Verification
Nithin Rao Koluguri, Jason Li, Vitaly Lavrukhin +1
We propose SpeakerNet - a new neural architecture for speaker recognition and speaker verification tasks. It is composed of residual blocks with 1D depth-wise separable convolution…
Cross-Language Transfer Learning, Continuous Learning, and Domain Adaptation for End-to-End Automatic Speech Recognition
Jocelyn Huang, Oleksii Kuchaiev, Patrick O'Neill +5
In this paper, we demonstrate the efficacy of transfer learning and continuous learning for various automatic speech recognition (ASR) tasks. We start with a pre-trained English AS…
QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions
Samuel Kriman, Stanislav Beliaev, Boris Ginsburg +6
We propose a new end-to-end neural acoustic model for automatic speech recognition. The model is composed of multiple blocks with residual connections between them. Each block cons…
Jasper: An End-to-End Convolutional Neural Acoustic Model
Jason Li, Vitaly Lavrukhin, Boris Ginsburg +5
In this paper, we report state-of-the-art results on LibriSpeech among end-to-end speech recognition models without any external training data. Our model, Jasper, uses only 1D conv…