Robert Gmyr

Research Software Development Engineer

出版物

表示方法:

- i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
  
  Ziyi Yang, Mahmoud Khademi, Yichong Xu, Reid Pryzant, Yuwei Fang, Chenguang Zhu, Dongdong Chen, Yao Qian, Mei Gao, Yi-Ling Chen, Robert Gmyr, Naoyuki Kanda, Noel Codella, Bin Xiao, Yu Shi, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang
  
  North American Chapter of the Association for Computational Linguistics (NAACL) 2024 | May 2023
  
  Publication
- Knowledge Distillation for Mixture of Experts Models in Speech Recognition
  
  Felipe Cruz Salinas, Kenichi Kumatani, Robert Gmyr, Linquan Liu, Yu Shi
  
  MSR-TR-2022-6 | May 2022
  
  Microsoft による投稿
  
  Publication
- Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition
  
  Kenichi Kumatani, Robert Gmyr, Felipe Cruz Salinas, Linquan Liu, Wei Zuo , Devang Patel, Eric Sun, Yu Shi
  
  CoRR | December 2021, 巻abs/2112.05820
  
  Publication
- One-Shot Voice Conversion with Speaker-Agnostic StarGAN
  
  Sefik Emre Eskimez, Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr
  
  INTERSPEECH 2022 | August 2021
  
  Publication DOI プロジェクト
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  2021 International ACM SIGIR Conference on Research and Development in Information Retrieval | July 2021
  
  PDF Publication
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021. | July 2021
  
  Publication
- TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
  
  Empirical Methods in Natural Language Processing (EMNLP) | November 2020
  
  Publication
- Sequence-Level Self-Learning with Multiple Hypotheses
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  Interspeech | October 2020
  
  Publication DOI プロジェクト
- A Federated Approach in Training Acoustic Models
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- GAN-based Data Generation for Speech Emotion Recognition
  
  Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- Sequence-level self-learning with multi-task learning framework
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  October 2020
  
  プロジェクト
- Federated Transfer Learning with Dynamic Gradient Aggregation
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  August 2020
  
  Publication プロジェクト
- TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.
  
  Ziyi Yang, Chenguang Zhu, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
  
  2020 Empirical Methods in Natural Language Processing | March 2020
  
  DOI Publication
- Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  arXiv 1912.11602 | December 2019
  
  Publication

- i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
  
  Ziyi Yang, Mahmoud Khademi, Yichong Xu, Reid Pryzant, Yuwei Fang, Chenguang Zhu, Dongdong Chen, Yao Qian, Mei Gao, Yi-Ling Chen, Robert Gmyr, Naoyuki Kanda, Noel Codella, Bin Xiao, Yu Shi, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang
  
  North American Chapter of the Association for Computational Linguistics (NAACL) 2024 | May 2023
  
  Publication
- Knowledge Distillation for Mixture of Experts Models in Speech Recognition
  
  Felipe Cruz Salinas, Kenichi Kumatani, Robert Gmyr, Linquan Liu, Yu Shi
  
  MSR-TR-2022-6 | May 2022
  
  Microsoft による投稿
  
  Publication
- Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition
  
  Kenichi Kumatani, Robert Gmyr, Felipe Cruz Salinas, Linquan Liu, Wei Zuo , Devang Patel, Eric Sun, Yu Shi
  
  CoRR | December 2021, 巻abs/2112.05820
  
  Publication
- One-Shot Voice Conversion with Speaker-Agnostic StarGAN
  
  Sefik Emre Eskimez, Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr
  
  INTERSPEECH 2022 | August 2021
  
  Publication DOI プロジェクト
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  2021 International ACM SIGIR Conference on Research and Development in Information Retrieval | July 2021
  
  PDF Publication
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021. | July 2021
  
  Publication
- Sequence-Level Self-Learning with Multiple Hypotheses
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  Interspeech | October 2020
  
  Publication DOI プロジェクト
- Sequence-level self-learning with multi-task learning framework
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  October 2020
  
  プロジェクト
- GAN-based Data Generation for Speech Emotion Recognition
  
  Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- A Federated Approach in Training Acoustic Models
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- Federated Transfer Learning with Dynamic Gradient Aggregation
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  August 2020
  
  Publication プロジェクト
- TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.
  
  Ziyi Yang, Chenguang Zhu, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
  
  2020 Empirical Methods in Natural Language Processing | March 2020
  
  DOI Publication
- i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
  
  Ziyi Yang, Mahmoud Khademi, Yichong Xu, Reid Pryzant, Yuwei Fang, Chenguang Zhu, Dongdong Chen, Yao Qian, Mei Gao, Yi-Ling Chen, Robert Gmyr, Naoyuki Kanda, Noel Codella, Bin Xiao, Yu Shi, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang
  
  North American Chapter of the Association for Computational Linguistics (NAACL) 2024 | May 2023
  
  Publication
- i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
  
  Ziyi Yang, Mahmoud Khademi, Yichong Xu, Reid Pryzant, Yuwei Fang, Chenguang Zhu, Dongdong Chen, Yao Qian, Mei Gao, Yi-Ling Chen, Robert Gmyr, Naoyuki Kanda, Noel Codella, Bin Xiao, Yu Shi, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang
  
  North American Chapter of the Association for Computational Linguistics (NAACL) 2024 | May 2023
  
  Publication
- i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
  
  Ziyi Yang, Mahmoud Khademi, Yichong Xu, Reid Pryzant, Yuwei Fang, Chenguang Zhu, Dongdong Chen, Yao Qian, Mei Gao, Yi-Ling Chen, Robert Gmyr, Naoyuki Kanda, Noel Codella, Bin Xiao, Yu Shi, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang
  
  North American Chapter of the Association for Computational Linguistics (NAACL) 2024 | May 2023
  
  Publication
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  2021 International ACM SIGIR Conference on Research and Development in Information Retrieval | July 2021
  
  PDF Publication
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021. | July 2021
  
  Publication
- TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
  
  Empirical Methods in Natural Language Processing (EMNLP) | November 2020
  
  Publication
- TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.
  
  Ziyi Yang, Chenguang Zhu, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
  
  2020 Empirical Methods in Natural Language Processing | March 2020
  
  DOI Publication
- Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  arXiv 1912.11602 | December 2019
  
  Publication
- Sequence-level self-learning with multi-task learning framework
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  October 2020
  
  プロジェクト
- Federated Transfer Learning with Dynamic Gradient Aggregation
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  August 2020
  
  Publication プロジェクト
- Sequence-level self-learning with multi-task learning framework
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  October 2020
  
  プロジェクト
- GAN-based Data Generation for Speech Emotion Recognition
  
  Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- A Federated Approach in Training Acoustic Models
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- Federated Transfer Learning with Dynamic Gradient Aggregation
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  August 2020
  
  Publication プロジェクト
- A Federated Approach in Training Acoustic Models
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- Federated Transfer Learning with Dynamic Gradient Aggregation
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  August 2020
  
  Publication プロジェクト

- i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
  
  Ziyi Yang, Mahmoud Khademi, Yichong Xu, Reid Pryzant, Yuwei Fang, Chenguang Zhu, Dongdong Chen, Yao Qian, Mei Gao, Yi-Ling Chen, Robert Gmyr, Naoyuki Kanda, Noel Codella, Bin Xiao, Yu Shi, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang
  
  North American Chapter of the Association for Computational Linguistics (NAACL) 2024 | May 2023
  
  Publication
- One-Shot Voice Conversion with Speaker-Agnostic StarGAN
  
  Sefik Emre Eskimez, Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr
  
  INTERSPEECH 2022 | August 2021
  
  Publication DOI プロジェクト
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  2021 International ACM SIGIR Conference on Research and Development in Information Retrieval | July 2021
  
  PDF Publication
- Leveraging Lead Bias for Zero-shot Abstractive News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021. | July 2021
  
  Publication
- Sequence-Level Self-Learning with Multiple Hypotheses
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  Interspeech | October 2020
  
  Publication DOI プロジェクト
- GAN-based Data Generation for Speech Emotion Recognition
  
  Sefik Emre Eskimez, Dimitrios Dimitriadis, Robert Gmyr, Kenichi Kumatani
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- A Federated Approach in Training Acoustic Models
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  INTERSPEECH 2020 | October 2020
  
  Publication プロジェクト
- TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.
  
  Ziyi Yang, Chenguang Zhu, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
  
  2020 Empirical Methods in Natural Language Processing | March 2020
  
  DOI Publication
- Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition
  
  Kenichi Kumatani, Robert Gmyr, Felipe Cruz Salinas, Linquan Liu, Wei Zuo , Devang Patel, Eric Sun, Yu Shi
  
  CoRR | December 2021, 巻abs/2112.05820
  
  Publication
- TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang, Eric Darve
  
  Empirical Methods in Natural Language Processing (EMNLP) | November 2020
  
  Publication
- Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization
  
  Chenguang Zhu, Ziyi Yang, Robert Gmyr, Michael Zeng, Xuedong Huang
  
  arXiv 1912.11602 | December 2019
  
  Publication
- Knowledge Distillation for Mixture of Experts Models in Speech Recognition
  
  Felipe Cruz Salinas, Kenichi Kumatani, Robert Gmyr, Linquan Liu, Yu Shi
  
  MSR-TR-2022-6 | May 2022
  
  Microsoft による投稿
  
  Publication
- Federated Transfer Learning with Dynamic Gradient Aggregation
  
  Dimitrios Dimitriadis, Kenichi Kumatani, Robert Gmyr, Yashesh Gaur, Sefik Emre Eskimez
  
  August 2020
  
  Publication プロジェクト
- Sequence-level self-learning with multi-task learning framework
  
  Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur, Robert Gmyr, Sefik Emre Eskimez, Jinyu Li, Michael Zeng
  
  October 2020
  
  プロジェクト

Robert Gmyr

出版物

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

Knowledge Distillation for Mixture of Experts Models in Speech Recognition

Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition

One-Shot Voice Conversion with Speaker-Agnostic StarGAN

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising

Sequence-Level Self-Learning with Multiple Hypotheses

A Federated Approach in Training Acoustic Models

GAN-based Data Generation for Speech Emotion Recognition

Sequence-level self-learning with multi-task learning framework

Federated Transfer Learning with Dynamic Gradient Aggregation

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.

Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

Knowledge Distillation for Mixture of Experts Models in Speech Recognition

Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition

One-Shot Voice Conversion with Speaker-Agnostic StarGAN

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

Sequence-Level Self-Learning with Multiple Hypotheses

Sequence-level self-learning with multi-task learning framework

GAN-based Data Generation for Speech Emotion Recognition

A Federated Approach in Training Acoustic Models

Federated Transfer Learning with Dynamic Gradient Aggregation

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.

Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization

Sequence-level self-learning with multi-task learning framework

Federated Transfer Learning with Dynamic Gradient Aggregation

Sequence-level self-learning with multi-task learning framework

GAN-based Data Generation for Speech Emotion Recognition

A Federated Approach in Training Acoustic Models

Federated Transfer Learning with Dynamic Gradient Aggregation

A Federated Approach in Training Acoustic Models

Federated Transfer Learning with Dynamic Gradient Aggregation

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

One-Shot Voice Conversion with Speaker-Agnostic StarGAN

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

Leveraging Lead Bias for Zero-shot Abstractive News Summarization

Sequence-Level Self-Learning with Multiple Hypotheses

GAN-based Data Generation for Speech Emotion Recognition

A Federated Approach in Training Acoustic Models

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.

Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising

Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization

Knowledge Distillation for Mixture of Experts Models in Speech Recognition

Federated Transfer Learning with Dynamic Gradient Aggregation

Sequence-level self-learning with multi-task learning framework