Rebecca R Vos

Rebecca R Vos

Imperial College London

H-index: 4

Europe-United Kingdom

About Rebecca R Vos

Rebecca R Vos, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at Imperial College London, specializes in the field of speech processing, hearing impairment, singing voice.

His recent articles reflect a diverse array of research interests and contributions to the field:

Using a single-channel reference with the MBSTOI binaural intelligibility metric

A systematic review of measurements of real-world interior car noise for the “Cadenza” machine-learning project

Towards Integration of Biosensors and Hearing Aids for Music

The First Cadenza Signal Processing Challenge: Improving Music for Those With a Hearing Loss

The Cadenza ICASSP 2024 Grand Challenge

The MBSTOI Binaural Intelligibility Metric Using a Close-Talking Microphone Reference

Machine learning for parameter estimation in the MBSTOI binaural intelligibility metric

A compact noise covariance matrix model for MVDR beamforming

Rebecca R Vos Information

University

Position

Research Associate

Citations(all)

62

Citations(since 2020)

46

Cited By

22

hIndex(all)

4

hIndex(since 2020)

4

i10Index(all)

3

i10Index(since 2020)

1

Email

University Profile Page

Imperial College London

Google Scholar

View Google Scholar Profile

Rebecca R Vos Skills & Research Interests

speech processing

hearing impairment

singing voice

Top articles of Rebecca R Vos

Title

Journal

Author(s)

Publication Date

Using a single-channel reference with the MBSTOI binaural intelligibility metric

Speech Communication

Pierre Guiraud

Alastair H Moore

Rebecca R Vos

Patrick A Naylor

Mike Brookes

2023/4/1

A systematic review of measurements of real-world interior car noise for the “Cadenza” machine-learning project

Jennifer L Firth

Trevor J Cox

Alinka Greasley

Jon P Barker

William M Whitmer

...

2023/3/1

Towards Integration of Biosensors and Hearing Aids for Music

Rory Stocks

Duncan Williams

Rebecca R Vos

Trevor Cox

2023/12/4

The First Cadenza Signal Processing Challenge: Improving Music for Those With a Hearing Loss

arXiv preprint arXiv:2310.05799

Gerardo Roa Dabike

Scott Bannister

Jennifer Firth

Simone Graetzer

Rebecca Vos

...

2023/10/9

The Cadenza ICASSP 2024 Grand Challenge

arXiv preprint arXiv:2310.03480

Gerardo Roa Dabike

Michael A Akeroyd

Scott Bannister

Jon Barker

Trevor J Cox

...

2023/10/5

The MBSTOI Binaural Intelligibility Metric Using a Close-Talking Microphone Reference

Pierre Guiraud

Alastair H Moore

Rebecca R Vos

Patrick A Naylor

Mike Brookes

2023/6/4

Machine learning for parameter estimation in the MBSTOI binaural intelligibility metric

Pierre Guiraud

Alastair H Moore

Rebecca R Vos

Patrick A Naylor

Mike Brookes

2022/9/5

A compact noise covariance matrix model for MVDR beamforming

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Alastair H Moore

Sina Hafezi

Rebecca R Vos

Patrick A Naylor

Mike Brookes

2022/6/7

Evaluation of noise excitation as a method for detection of hypernasality

Applied Acoustics

Kat Young

Triona Sweeney

Rebecca R Vos

Felicity Mehendale

Helena Daffern

2022/3/15

Processing pipelines for efficient, physically-accurate simulation of microphone array signals in dynamic sound scenes

Alastair H Moore

Rebecca R Vos

Patrick A Naylor

Mike Brookes

2021/6/6

ELO-SPHERES consortium system description

Proc. of Clarity

Alastair H Moore

Sina Hafezi

Rebecca Vos

Mike Brookes

Patrick A Naylor

...

2021

A binaural MVDR beamformer for the 2021 Clarity Enhancement Challenge: ELO-SPHERES consortium system description

Proc. Clarity Workshop on Machine Learning Challenges for Hearing Aids

Alastair H Moore

Sina Hafezi

Rebecca Vos

Mike Brookes

Patrick A Naylor

...

2021

See List of Professors in Rebecca R Vos University(Imperial College London)