IDiyas

For the Inventor, By the Inventor

New York, NY, United States of America

Ron J Weiss

USPTO Granted Patents = 42 

 

 

Average Co-Inventor Count = 5.8

ph-index = 6

Forward Citations = 326(Granted Patents)


Company Filing History:

goldMedal42 out of 32,429 
 
Google Inc.
 patents

Years Active: 2012-2025

where 'Filed Patents' based on already Granted Patents

42 patents (USPTO):
1. 12488780 - Parallel tacotron non-autoregressive and controllable TTS (2025-12-02),
2. 12400633 - End-to-end speech waveform generation through data density gradient estimation (2025-08-26),
3. 12300216 - End-to-end speech conversion (2025-05-13),
4. 12254865 - Multi-dialect and multilingual speech recognition (2025-03-18),
5. 12190860 - End-to-end text-to-speech conversion (2025-01-07),
6. 12175963 - Synthesis of speech from text in a voice of a target speaker using neural networks (2024-12-24),
7. 12148444 - Synthesizing speech from text using neural networks (2024-11-19),
8. 12106749 - Speech recognition with sequence-to-sequence models (2024-10-01),
9. 12087273 - Multilingual speech synthesis and cross-language voice cloning (2024-09-10),
10. 12032920 - Direct speech-to-speech translation via machine learning (2024-07-09),
11. 11908448 - Parallel tacotron non-autoregressive and controllable TTS (2024-02-20),
12. 11900915 - Multi-dialect and multilingual speech recognition (2024-02-13),
13. 11862142 - End-to-end text-to-speech conversion (2024-01-02),
14. 11848002 - Synthesis of speech from text in a voice of a target speaker using neural networks (2023-12-19),
15. 11783849 - Enhanced multi-channel acoustic models (2023-10-10),

Title: Ron J Weiss: Innovator in Text-to-Speech Technologies

Introduction

Ron J Weiss, based in New York, NY, is a prominent inventor in the field of speech synthesis and natural language processing. With an impressive portfolio of 38 patents, Weiss has significantly contributed to advancements in technology that facilitate the conversion of text into human-like speech.

Latest Patents

Among his latest patents is the innovative system for end-to-end text-to-speech conversion. This invention encompasses methods, systems, and apparatus, including computer programs encoded on storage media, aimed at generating speech from text. The framework includes one or more computers and storage devices that execute instructions to implement a sequence-to-sequence recurrent neural network. This technology is designed to receive a sequence of characters in a specific natural language and process it to generate a spectrogram of the corresponding verbal utterance.

Another significant patent by Weiss focuses on the synthesis of speech from text using a voice of a target speaker through neural networks. This invention encapsulates methods and systems that include obtaining an audio representation of a target speaker’s voice and input text. It generates a speaker vector and leverages this alongside the input text to produce an audio representation of the spoken text in the target speaker’s voice.

Career Highlights

Weiss's tenure at Google Inc. has been marked by substantial innovations that push the boundaries of artificial intelligence and machine learning. His inventions in speech synthesis have not only enhanced user experience across various applications but have also set new standards in the industry. His continuous pursuit of improvement in natural language processing has positioned him as a key figure in technological advancements within the company.

Collaborations

Throughout his career, Ron J Weiss has collaborated with esteemed colleagues such as Yonghui Wu and Tara N Sainath. These collaborations have fostered a research environment that encourages innovative thinking and the development of state-of-the-art speech synthesis technologies.

Conclusion

Ron J Weiss’s contributions to the field of speech synthesis and natural language processing are invaluable. His innovative patents reflect a deep commitment to enhancing how machines understand and generate human language. As technology continues to evolve, Weiss’s work will undoubtedly influence future advancements in this dynamic field.

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