Kyle Kastner

According to our database, Kyle Kastner authored at least 21 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Zero-shot Cross-lingual Voice Transfer for TTS.

Fadi Biadsy, Youzheng Chen, Isaac Elias, Kyle Kastner, Gary Wang, Andrew Rosenberg, Bhuvana Ramabhadran

CoRR, 2024

Adversarial training of Keyword Spotting to Minimize TTS Data Overfitting.

Hyun Jin Park, Dhruuv Agarwal, Neng Chen, Rentao Sun, Kurt Partridge, Justin Chen, Harry Zhang, Pai Zhu, Jacob Bartel, Kyle Kastner, Gary Wang, Andrew Rosenberg, Quan Wang

CoRR, 2024

Utilizing TTS Synthesized Data for Efficient Development of Keyword Spotting Model.

Hyun Jin Park, Dhruuv Agarwal, Neng Chen, Rentao Sun, Kurt Partridge, Justin Chen, Harry Zhang, Pai Zhu, Jacob Bartel, Kyle Kastner, Gary Wang, Andrew Rosenberg, Quan Wang

CoRR, 2024

High-precision Voice Search Query Correction via Retrievable Speech-text Embedings.

Christopher Li, Gary Wang, Kyle Kastner, Heng Su, Allen Chen, Andrew Rosenberg, Zhehuai Chen, Zelin Wu, Leonid Velikovich, Pat Rondon, Diamantino Caseiro, Petar S. Aleksic

CoRR, 2024

Adaptive Accompaniment with ReaLchords.

Yusong Wu, Tim Cooijmans, Kyle Kastner, Adam Roberts, Ian Simon, Alexander Scarlatos, Chris Donahue, Cassie Tarakajian, Shayegan Omidshafiei, Aaron C. Courville, Pablo Samuel Castro, Natasha Jaques, Cheng-Zhi Anna Huang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Extending Multilingual Speech Synthesis to 100+ Languages without Transcribed Data.

Takaaki Saeki, Gary Wang, Nobuyuki Morioka, Isaac Elias, Kyle Kastner, Andrew Rosenberg, Bhuvana Ramabhadran, Heiga Zen, Françoise Beaufays, Hadar Shemtov

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Understanding Shared Speech-Text Representations.

Gary Wang, Kyle Kastner, Ankur Bapna, Zhehuai Chen, Andrew Rosenberg, Bhuvana Ramabhadran, Yu Zhang

Proceedings of the IEEE International Conference on Acoustics, 2023

SUNMASK: Mask Enhanced Control in Step Unrolled Denoising Autoencoders.

Kyle Kastner, Tim Cooijmans, Yusong Wu, Aaron C. Courville

Proceedings of the Artificial Intelligence in Music, Sound, Art and Design, 2023

2022

R-MelNet: Reduced Mel-Spectral Modeling for Neural TTS.

Kyle Kastner, Aaron C. Courville

CoRR, 2022

MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling.

Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron C. Courville, Cheng-Zhi Anna Huang, Jesse H. Engel

Proceedings of the Tenth International Conference on Learning Representations, 2022

2019

Representation Mixing for TTS Synthesis.

Kyle Kastner, João Felipe Santos, Yoshua Bengio, Aaron C. Courville

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Planning in Dynamic Environments with Conditional Autoregressive Models.

Johanna Hansen, Kyle Kastner, Aaron C. Courville, Gregory Dudek

CoRR, 2018

Harmonic Recomposition using Conditional Autoregressive Modeling.

Kyle Kastner, Rithesh Kumar, Tim Cooijmans, Aaron C. Courville

CoRR, 2018

Blindfold Baselines for Embodied QA.

Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville

CoRR, 2018

2017

Learning to Discover Sparse Graphical Models.

Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko

Proceedings of the 34th International Conference on Machine Learning, 2017

Char2Wav: End-to-End Speech Synthesis.

Jose Sotelo, Soroush Mehri, Kundan Kumar, João Felipe Santos, Kyle Kastner, Aaron C. Courville, Yoshua Bengio

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation.

Francesco Visin, Adriana Romero, Kyunghyun Cho, Matteo Matteucci, Marco Ciccone, Kyle Kastner, Yoshua Bengio, Aaron C. Courville

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

2015

ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks.

Francesco Visin, Kyle Kastner, Kyunghyun Cho, Matteo Matteucci, Aaron C. Courville, Yoshua Bengio

CoRR, 2015

ReSeg: A Recurrent Neural Network for Object Segmentation.

Francesco Visin, Kyle Kastner, Aaron C. Courville, Yoshua Bengio, Matteo Matteucci, KyungHyun Cho

CoRR, 2015

Learning Distributed Representations from Reviews for Collaborative Filtering.

Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

A Recurrent Latent Variable Model for Sequential Data.

Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C. Courville, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015