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Ron Weiss

Ron Weiss

D-Index & Metrics

Computer Science

D-Index
84
Citations
109587
World Ranking
816
National Ranking
443

Overview

Ron Weiss is affiliated with MIT in the United States and has contributed extensively to the field of computer science, with a focus on artificial intelligence, signal processing, and related subfields.

Their research spans several main topics including:

  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Natural Language Processing Techniques
  • Topic Modeling
  • Speech and Audio Processing
  • Music Technology and Sound Studies
  • Model Reduction and Neural Networks

Ron Weiss has published a number of papers, primarily disseminated through arXiv at Cornell University and other venues such as the 2022 IEEE Spoken Language Technology Workshop (SLT). Notable recent papers include:

  • "Unsupervised Sound Separation Using Mixture Invariant Training", 2020, arXiv (Cornell University)
  • "WaveGrad: Estimating Gradients for Waveform Generation", 2020, arXiv (Cornell University)
  • "Parallel Tacotron: Non-Autoregressive and Controllable TTS", 2020, arXiv (Cornell University)
  • "Generating diverse and natural text-to-speech samples using a quantized fine-grained VAE and auto-regressive prosody prior", 2020, arXiv (Cornell University)
  • "Fully-hierarchical fine-grained prosody modeling for interpretable speech synthesis", 2020, arXiv (Cornell University)

The majority of their publications are found in arXiv (Cornell University), with a total of nine papers in this venue, complemented by other contributions such as to the 2022 IEEE Spoken Language Technology Workshop.

Frequent collaborators include:

  • Heiga Zen (5 coauthored papers)
  • Bhuvana Ramabhadran (3 coauthored papers)
  • Yonghui Wu (3 coauthored papers)
  • Yu Zhang (3 coauthored papers)
  • Guangzhi Sun (2 coauthored papers)

Ron Weiss's work largely focuses on advanced methodologies in speech synthesis and sound processing. The development of models and techniques within speech and audio processing, combined with expertise in natural language processing, illustrates a cross-disciplinary approach to computational audio and language technologies.

Their contributions include exploration of neural network models for waveform generation and prosody modeling, as well as unsupervised separation of sound sources, offering insight into complex audio signal processing tasks.

Best Publications

  • Scikit-learn: Machine Learning in Python

    Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel

  • Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions

    Jonathan Shen;Ruoming Pang;Ron J. Weiss;Mike Schuster

  • CNN architectures for large-scale audio classification

    Shawn Hershey;Sourish Chaudhuri;Daniel P. W. Ellis;Jort F. Gemmeke

  • Tacotron: Towards End-to-End Speech Synthesis

    Yuxuan Wang;R. J. Skerry-Ryan;Daisy Stanton;Yonghui Wu

  • Highly efficient Cas9-mediated transcriptional programming

    Alejandro Chavez;Jonathan Scheiman;Suhani Vora;Benjamin W Pruitt

  • The second wave of synthetic biology: from modules to systems

    Priscilla E. M. Purnick;Ron Weiss

  • Synthetic biology: new engineering rules for an emerging discipline

    Ernesto Andrianantoandro;Subhayu Basu;David K Karig;Ron Weiss

  • State-of-the-Art Speech Recognition with Sequence-to-Sequence Models

    Chung-Cheng Chiu;Tara N. Sainath;Yonghui Wu;Rohit Prabhavalkar

  • Amorphous computing

    Harold Abelson;Don Allen;Daniel Coore;Chris Hanson

  • LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech

    Heiga Zen;Viet Dang;Rob Clark;Yu Zhang

  • Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis

    Ye Jia;Yu Zhang;Ron J. Weiss;Quan Wang

  • Scikit-learn: Machine Learning in Python

    Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel

  • A universal RNAi-based logic evaluator that operates in mammalian cells

    Keller Rinaudo;Leonidas Bleris;Rohan Maddamsetti;Sairam Subramanian

  • Learning the Speech Front-end with Raw Waveform CLDNNs

    Tara N. Sainath;Ron J. Weiss;Andrew W. Senior;Kevin W. Wilson

  • Directed evolution of a genetic circuit

    Yohei Yokobayashi;Ron Weiss;Frances H. Arnold

  • HyPursuit: a hierarchical network search engine that exploits content-link hypertext clustering

    Ron Weiss;Bienvenido Vélez;Mark A. Sheldon

  • Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron

    RJ Skerry-Ryan;Eric Battenberg;Ying Xiao;Yuxuan Wang

  • Model-Based Expectation-Maximization Source Separation and Localization

    M.I. Mandel;R.J. Weiss;D. Ellis

  • VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking

    Hannah Raphaelle Muckenhirn;Ignacio Lopez Moreno;John Hershey;Kevin Wilson

  • Cas9 gRNA engineering for genome editing, activation and repression

    Samira Kiani;Alejandro Chavez;Alejandro Chavez;Marcelle Tuttle;Richard N Hall

  • Sequence-to-Sequence Models Can Directly Translate Foreign Speech

    Ron J. Weiss;Jan Chorowski;Navdeep Jaitly;Yonghui Wu

  • Highly efficient Cas9-mediated transcriptional programming

    Alejandro Chavez;Jonathan Scheiman;Marcelle Tuttle;Shuailiang Lin

Frequent Co-Authors

Yonghui Wu
Yonghui Wu Google (United States)
Zhifeng Chen
Zhifeng Chen Google (United States)
Tara N. Sainath
Tara N. Sainath Google (United States)
Jacob Beal
Jacob Beal Raytheon (United States)
Daniel P. W. Ellis
Daniel P. W. Ellis Google (United States)
George M. Church
George M. Church Harvard University
Navdeep Jaitly
Navdeep Jaitly Google (United States)
Michiel Bacchiani
Michiel Bacchiani Google (United States)
Yuxuan Wang
Yuxuan Wang ByteDance
Heiga Zen
Heiga Zen Google (United States)

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