Fileno A Alleva

This inventor holds 23 USPTO granted patents and 1 published patent application and 1 EPO patent. Top assignees: Microsoft Technology Licensing, LLC, Micrsoft Corporation. Active years: 1998-2021.

USPTO Granted Patents = 23 (Patent Applications = 1)

% Patents Active = 82.6

EPO Patents = 1 (Patent Applications = 4)

Average Co-Inventor Count = 2.9

ph-index = 16

Forward Citations = 1,509(Granted Patents)

Company Filing History:

22 out of 56,215

Microsoft Technology Licensing, LLC

Years Active: 1998-2021

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23 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 10957337 - Multi-microphone speech separation (2021-03-23),

2. 10127901 - Hyper-structure recurrent neural networks for text-to-speech (2018-11-13),

3. 9263030 - Adaptive online feature normalization for speech recognition (2016-02-16),

4. 9098494 - Building multi-language processes from existing single-language processes (2015-08-04),

5. 8352270 - Interactive TTS optimization tool (2013-01-08),

6. 7676365 - Method and apparatus for constructing and using syllable-like unit language models (2010-03-09),

7. 7251600 - Disambiguation language model (2007-07-31),

8. 7162423 - Method and apparatus for generating and displaying N-Best alternatives in a speech recognition system (2007-01-09),

9. 7016838 - Method and system for frame alignment and unsupervised adaptation of acoustic models (2006-03-21),

10. 6973427 - Method for adding phonetic descriptions to a speech recognition lexicon (2005-12-06),

11. 6934683 - Disambiguation language model (2005-08-23),

12. 6917918 - Method and system for frame alignment and unsupervised adaptation of acoustic models (2005-07-12),

13. 6856956 - Method and apparatus for generating and displaying N-best alternatives in a speech recognition system (2005-02-15),

14. 6694296 - Method and apparatus for the recognition of spelled spoken words (2004-02-17),

15. 6336108 - Speech recognition with mixtures of bayesian networks (2002-01-01),

Title: Fileno A. Alleva: Innovator in Speech Technology

Introduction

Fileno A. Alleva is a distinguished inventor based in Redmond, WA, with a strong portfolio of 23 patents to his name. His innovations primarily focus on advancements in speech recognition and synthesis technologies, significantly contributing to the fields of artificial intelligence and machine learning.

Latest Patents

Alleva's latest patents demonstrate his expertise in audio processing and text-to-speech conversion. One of his notable inventions, titled "Multi-microphone speech separation," involves the separation of audio signals into individual speaker-specific signals. This technology utilizes features captured by multiple microphones, processed through a neural network, to create distinct outputs for each speaker.

Another key patent is "Hyper-structure recurrent neural networks for text-to-speech," which leverages recurrent neural networks (RNNs) to convert text into audible speech. This innovative approach incorporates various RNN modules that analyze properties of the text, ultimately processed by a hyper-structure RNN module to optimize the generation sequence for the speech synthesizer.

Career Highlights

Throughout his career, Alleva has been affiliated with major tech companies, including Microsoft Technology Licensing, LLC, and Microsoft Corporation. His work in these organizations has allowed him to contribute significantly to advancements in speech technology and artificial intelligence.

Collaborations

Fileno A. Alleva has collaborated with renowned professionals in the industry, such as Mei-Yuh Hwang and David Earl Heckerman. These partnerships have facilitated the development of innovative solutions and have furthered research in speech processing technologies.

Conclusion

Fileno A. Alleva's contributions to the fields of speech technology and artificial intelligence highlight his role as a key innovator. With a robust portfolio of patents and collaborative efforts with other experts, he continues to pave the way for advancements that enhance communication and interaction through technology.