Search Results for author: Chris Donahue

Found 15 papers, 12 papers with code

It's Raw! Audio Generation with State-Space Models

2 code implementations20 Feb 2022 Karan Goel, Albert Gu, Chris Donahue, Christopher Ré

SaShiMi yields state-of-the-art performance for unconditional waveform generation in the autoregressive setting.

Audio Generation Density Estimation +1

On the Opportunities and Risks of Foundation Models

no code implementations16 Aug 2021 Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, aditi raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

AI is undergoing a paradigm shift with the rise of models (e. g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.

Transfer Learning

Towards Automatic Instrumentation by Learning to Separate Parts in Symbolic Multitrack Music

1 code implementation13 Jul 2021 Hao-Wen Dong, Chris Donahue, Taylor Berg-Kirkpatrick, Julian McAuley

In this paper, we aim to further extend this idea and examine the feasibility of automatic instrumentation -- dynamically assigning instruments to notes in solo music during performance.

Multi-class Classification

Codified audio language modeling learns useful representations for music information retrieval

1 code implementation12 Jul 2021 Rodrigo Castellon, Chris Donahue, Percy Liang

Relative to representations from conventional MIR models which are pre-trained on tagging, we find that using representations from Jukebox as input features yields 30% stronger performance on average across four MIR tasks: tagging, genre classification, emotion recognition, and key detection.

Emotion Recognition Genre classification +7

Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality

1 code implementation NAACL 2021 Mina Lee, Chris Donahue, Robin Jia, Alexander Iyabor, Percy Liang

We release a new benchmark for lexical substitution, the task of finding appropriate substitutes for a target word in a context.

Enabling Language Models to Fill in the Blanks

3 code implementations ACL 2020 Chris Donahue, Mina Lee, Percy Liang

We show that this approach, which we call infilling by language modeling, can enable LMs to infill entire sentences effectively on three different domains: short stories, scientific abstracts, and lyrics.

Language Modelling Text Infilling

Expediting TTS Synthesis with Adversarial Vocoding

1 code implementation16 Apr 2019 Paarth Neekhara, Chris Donahue, Miller Puckette, Shlomo Dubnov, Julian McAuley

Recent approaches in text-to-speech (TTS) synthesis employ neural network strategies to vocode perceptually-informed spectrogram representations directly into listenable waveforms.

GANSynth: Adversarial Neural Audio Synthesis

4 code implementations ICLR 2019 Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, Adam Roberts

Efficient audio synthesis is an inherently difficult machine learning task, as human perception is sensitive to both global structure and fine-scale waveform coherence.

Audio Generation

Piano Genie

no code implementations11 Oct 2018 Chris Donahue, Ian Simon, Sander Dieleman

We present Piano Genie, an intelligent controller which allows non-musicians to improvise on the piano.

The NES Music Database: A multi-instrumental dataset with expressive performance attributes

2 code implementations12 Jun 2018 Chris Donahue, Huanru Henry Mao, Julian McAuley

Existing research on music generation focuses on composition, but often ignores the expressive performance characteristics required for plausible renditions of resultant pieces.

Music Generation

Adversarial Audio Synthesis

18 code implementations ICLR 2019 Chris Donahue, Julian McAuley, Miller Puckette

Audio signals are sampled at high temporal resolutions, and learning to synthesize audio requires capturing structure across a range of timescales.

Audio Generation Image Generation

Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition

no code implementations15 Nov 2017 Chris Donahue, Bo Li, Rohit Prabhavalkar

We investigate the effectiveness of generative adversarial networks (GANs) for speech enhancement, in the context of improving noise robustness of automatic speech recognition (ASR) systems.

Automatic Speech Recognition Robust Speech Recognition +1

Dance Dance Convolution

1 code implementation ICML 2017 Chris Donahue, Zachary C. Lipton, Julian McAuley

For the step placement task, we combine recurrent and convolutional neural networks to ingest spectrograms of low-level audio features to predict steps, conditioned on chart difficulty.

Cannot find the paper you are looking for? You can Submit a new open access paper.