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Google at Interspeech 2019

This week, Graz, Austria hosts the 20th Annual Conference of the International Speech Communication Association (Interspeech 2019), one of the world‘s most extensive conferences on the research and engineering for spoken language processing. Over 2,000 experts in speech-related research fields gather to take part in oral presentations and poster sessions and to collaborate with streamed events across the globe.

As a Gold Sponsor of Interspeech 2019, we are excited to present 30 research publications, and demonstrate some of the impact speech technology has made in our products, from accessible, automatic video captioning to a more robust, reliable Google Assistant. If you’re attending Interspeech 2019, we hope that you’ll stop by the Google booth to meet our researchers and discuss projects and opportunities at Google that go into solving interesting problems for billions of people. Our researchers will also be on hand to discuss Google Cloud Text-to-Speech and Speech-to-text, demo Parrotron, and more. You can also learn more about the Google research being presented at Interspeech 2019 below (Google affiliations in blue).

Organizing Committee includes:
Michiel Bacchiani

Technical Program Committee includes:
Tara Sainath

Tutorials
Neural Machine Translation
Organizers include: Wolfgang Macherey, Yuan Cao

Accepted Publications
Building Large-Vocabulary ASR Systems for Languages Without Any Audio Training Data (link to appear soon)
Manasa Prasad, Daan van Esch, Sandy Ritchie, Jonas Fromseier Mortensen

Multi-Microphone Adaptive Noise Cancellation for Robust Hotword Detection (link to appear soon)
Yiteng Huang, Turaj Shabestary, Alexander Gruenstein, Li Wan

Direct Speech-to-Speech Translation with a Sequence-to-Sequence Model
Ye Jia, Ron Weiss, Fadi Biadsy, Wolfgang Macherey, Melvin Johnson, Zhifeng Chen, Yonghui Wu

Improving Keyword Spotting and Language Identification via Neural Architecture Search at Scale (link to appear soon)
Hanna Mazzawi, Javier Gonzalvo, Aleks Kracun, Prashant Sridhar, Niranjan Subrahmanya, Ignacio Lopez Moreno, Hyun Jin Park, Patrick Violette

Shallow-Fusion End-to-End Contextual Biasing (link to appear soon)
Ding Zhao, Tara Sainath, David Rybach, Pat Rondon, Deepti Bhatia, Bo Li, Ruoming Pang

VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
Quan Wang, Hannah Muckenhirn, Kevin Wilson, Prashant Sridhar, Zelin Wu, John Hershey, Rif Saurous, Ron Weiss, Ye Jia, Ignacio Lopez Moreno

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Daniel Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin Dogus Cubuk, Quoc Le

Two-Pass End-to-End Speech Recognition
Ruoming Pang, Tara Sainath, David Rybach, Yanzhang He, Rohit Prabhavalkar, Mirko Visontai, Qiao Liang, Trevor Strohman, Yonghui Wu, Ian McGraw, Chung-Cheng Chiu

On the Choice of Modeling Unit for Sequence-to-Sequence Speech Recognition
Kazuki Irie, Rohit Prabhavalkar, Anjuli Kannan, Antoine Bruguier, David Rybach, Patrick Nguyen

Contextual Recovery of Out-of-Lattice Named Entities in Automatic Speech Recognition (link to appear soon)
Jack Serrino, Leonid Velikovich, Petar Aleksic, Cyril Allauzen

Joint Speech Recognition and Speaker Diarization via Sequence Transduction
Laurent El Shafey, Hagen Soltau, Izhak Shafran

Personalizing ASR for Dysarthric and Accented Speech with Limited Data
Joel Shor, Dotan Emanuel, Oran Lang, Omry Tuval, Michael Brenner, Julie Cattiau, Fernando Vieira, Maeve McNally, Taylor Charbonneau, Melissa Nollstadt, Avinatan Hassidim, Yossi Matias

An Investigation Into On-Device Personalization of End-to-End Automatic Speech Recognition Models (link to appear soon)
Khe Chai Sim, Petr Zadrazil, Francoise Beaufays

Salient Speech Representations Based on Cloned Networks
Bastiaan Kleijn, Felicia Lim, Michael Chinen, Jan Skoglund

Cross-Lingual Consistency of Phonological Features: An Empirical Study (link to appear soon)
Cibu Johny, Alexander Gutkin, Martin Jansche

LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech
Heiga Zen, Viet Dang, Robert Clark, Yu Zhang, Ron Weiss, Ye Jia, Zhifeng Chen, Yonghui Wu

Improving Performance of End-to-End ASR on Numeric Sequences
Cal Peyser, Hao Zhang, Tara Sainath, Zelin Wu

Developing Pronunciation Models in New Languages Faster by Exploiting Common Grapheme-to-Phoneme Correspondences Across Languages (link to appear soon)
Harry Bleyan, Sandy Ritchie, Jonas Fromseier Mortensen, Daan van Esch

Phoneme-Based Contextualization for Cross-Lingual Speech Recognition in End-to-End Models
Ke Hu, Antoine Bruguier, Tara Sainath, Rohit Prabhavalkar, Golan Pundak

Fréchet Audio Distance: A Reference-free Metric for Evaluating Music Enhancement Algorithms
Kevin Kilgour, Mauricio Zuluaga, Dominik Roblek, Matthew Sharifi

Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning
Yu Zhang, Ron Weiss, Heiga Zen, Yonghui Wu, Zhifeng Chen, RJ Skerry-Ryan, Ye Jia, Andrew Rosenberg, Bhuvana Ramabhadran

Sampling from Stochastic Finite Automata with Applications to CTC Decoding
Martin Jansche, Alexander Gutkin

Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model (link to appear soon)
Anjuli Kannan, Arindrima Datta, Tara Sainath, Eugene Weinstein, Bhuvana Ramabhadran, Yonghui Wu, Ankur Bapna, Zhifeng Chen, SeungJi Lee

A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet
Jean-Marc Valin, Jan Skoglund

Low-Dimensional Bottleneck Features for On-Device Continuous Speech Recognition
David Ramsay, Kevin Kilgour, Dominik Roblek, Matthew Sharif

Unified Verbalization for Speech Recognition & Synthesis Across Languages (link to appear soon)
Sandy Ritchie, Richard Sproat, Kyle Gorman, Daan van Esch, Christian Schallhart, Nikos Bampounis, Benoit Brard, Jonas Mortensen, Amelia Holt, Eoin Mahon

Better Morphology Prediction for Better Speech Systems (link to appear soon)
Dravyansh Sharma, Melissa Wilson, Antoine Bruguier

Dual Encoder Classifier Models as Constraints in Neural Text Normalization
Ajda Gokcen, Hao Zhang, Richard Sproat

Large-Scale Visual Speech Recognition
Brendan Shillingford, Yannis Assael, Matthew Hoffman, Thomas Paine, Cían Hughes, Utsav Prabhu, Hank Liao, Hasim Sak, Kanishka Rao, Lorrayne Bennett, Marie Mulville, Ben Coppin, Ben Laurie, Andrew Senior, Nando de Freitas

Parrotron: An End-to-End Speech-to-Speech Conversion Model and its Applications to Hearing-Impaired Speech and Speech Separation
Fadi Biadsy, Ron Weiss, Pedro Moreno, Dimitri Kanevsky, Ye Jia

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.