351 citations · 990 across the 19 of their papers we have counts for
11 papers · 1 filter
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu +6
Neural network scaling has been critical for improving the model quality in many real-world machine learning applications with vast amounts of training data and compute. Although t…
A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency
Tara N. Sainath, Yanzhang He, Bo Li +26
Thus far, end-to-end (E2E) models have not been shown to outperform state-of-the-art conventional models with respect to both quality, i.e., word error rate (WER), and latency, i.e…
Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning
Yu Zhang, Ron J. Weiss, Heiga Zen +6
We present a multispeaker, multilingual text-to-speech (TTS) synthesis model based on Tacotron that is able to produce high quality speech in multiple languages. Moreover, the mode…
Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
Naveen Arivazhagan, Ankur Bapna, Orhan Firat +10
We introduce our efforts towards building a universal neural machine translation (NMT) system capable of translating between any language pair. We set a milestone towards this goal…
Gmail Smart Compose: Real-Time Assisted Writing
Mia Xu Chen, Benjamin N Lee, Gagan Bansal +9
In this paper, we present Smart Compose, a novel system for generating interactive, real-time suggestions in Gmail that assists users in writing mails by reducing repetitive typing…
Direct speech-to-speech translation with a sequence-to-sequence model
Ye Jia, Ron J. Weiss, Fadi Biadsy +4
We present an attention-based sequence-to-sequence neural network which can directly translate speech from one language into speech in another language, without relying on an inter…