activity
20182023
most citedLingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

184 citations · 239 across the 5 of their papers we have counts for

collaborators

6 papers

eess.AS2023

A Deliberation-based Joint Acoustic and Text Decoder

Sepand Mavandadi, Tara N. Sainath, Ke Hu +1

We propose a new two-pass E2E speech recognition model that improves ASR performance by training on a combination of paired data and unpaired text data. Previously, the joint acous…

cs.CL2022

Streaming Intended Query Detection using E2E Modeling for Continued Conversation

Shuo-yiin Chang, Guru Prakash, Zelin Wu +7

In voice-enabled applications, a predetermined hotword isusually used to activate a device in order to attend to the query.However, speaking queries followed by a hotword each time…

cs.CL2019

Speech Recognition with Augmented Synthesized Speech

Andrew Rosenberg, Yu Zhang, Bhuvana Ramabhadran +4

Recent success of the Tacotron speech synthesis architecture and its variants in producing natural sounding multi-speaker synthesized speech has raised the exciting possibility of…

eess.AS2019★ 5 cited

Improving Performance of End-to-End ASR on Numeric Sequences

Cal Peyser, Hao Zhang, Tara N. Sainath +1

Recognizing written domain numeric utterances (e.g. I need $1.25.) can be challenging for ASR systems, particularly when numeric sequences are not seen during training. This out-of…

cs.LG2019★ 184 cited

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Jonathan Shen, Patrick Nguyen, Yonghui Wu +88

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…

eess.AS2018★ 50 cited

VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking

Quan Wang, Hannah Muckenhirn, Kevin Wilson +7

In this paper, we present a novel system that separates the voice of a target speaker from multi-speaker signals, by making use of a reference signal from the target speaker. We ac…