Naomi Feldman

Naomi Feldman

University of Maryland, Baltimore

H-index: 21

North America-United States

About Naomi Feldman

Naomi Feldman, With an exceptional h-index of 21 and a recent h-index of 17 (since 2020), a distinguished researcher at University of Maryland, Baltimore, specializes in the field of Cognitive Science, Machine Learning, Speech Perception, Language Acquisition, Computational Psycholinguistics.

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

The competition–compensation account of developmental language disorder

Infant phonetic learning as perceptual space learning: A crosslinguistic evaluation of computational models

When children's production deviates from observed input: Modeling the variable production of the English past tense

Modeling substitution errors in Spanish morphology learning

A neural architecture for selective attention to speech features

Speech features are weighted by selective attention

Iterated learning models of language change: A case study of Sino‐Korean accent

Modeling the regular/irregular dissociation in non-fluent aphasia in a recurrent neural network

Naomi Feldman Information

University

Position

Associate Professor Linguistics and UMIACS

Citations(all)

1948

Citations(since 2020)

944

Cited By

1406

hIndex(all)

21

hIndex(since 2020)

17

i10Index(all)

28

i10Index(since 2020)

22

Email

University Profile Page

University of Maryland, Baltimore

Google Scholar

View Google Scholar Profile

Naomi Feldman Skills & Research Interests

Cognitive Science

Machine Learning

Speech Perception

Language Acquisition

Computational Psycholinguistics

Top articles of Naomi Feldman

Title

Journal

Author(s)

Publication Date

The competition–compensation account of developmental language disorder

Developmental Science

Zara Harmon

Libby Barak

Patrick Shafto

Jan Edwards

Naomi H Feldman

2023/7

Infant phonetic learning as perceptual space learning: A crosslinguistic evaluation of computational models

Cognitive Science

Yevgen Matusevych

Thomas Schatz

Herman Kamper

Naomi H Feldman

Sharon Goldwater

2023/7

When children's production deviates from observed input: Modeling the variable production of the English past tense

Cognitive Science

Libby Barak

Zara Harmon

Naomi H Feldman

Jan Edwards

Patrick Shafto

2023/8

Modeling substitution errors in Spanish morphology learning

Proceedings of the 45th Annual Conference of the Cognitive Science Society

Libby Barak

Nathalie Fernandez Echeverri

Naomi H Feldman

Patrick Shafto

2023

A neural architecture for selective attention to speech features

Proceedings of Interspeech

Nika Jurov

William Idsardi

Naomi H Feldman

2023/8

Speech features are weighted by selective attention

Proceedings of the Conference on Cognitive Computational Neuroscience

Nika Jurov

Grayson Wolf

William Idsardi

Naomi H Feldman

2023/8

Iterated learning models of language change: A case study of Sino‐Korean accent

Cognitive Science

Chiyuki Ito

Naomi H Feldman

2022/4

Modeling the regular/irregular dissociation in non-fluent aphasia in a recurrent neural network

Proceedings of the Annual Meeting of the Cognitive Science Society

Alexandra Krauska

Naomi H Feldman

2022

Assessing the learnability of process interactions using grammatical spaces

Proceedings of the Annual Meeting of the Cognitive Science Society

Christopher Yang

Adam Albright

Naomi H Feldman

2022

The power of ignoring: Filtering input for argument structure acquisition

Cognitive Science

Laurel Perkins

Naomi H Feldman

Jeffrey Lidz

2022/1

Naturalistic speech supports distributional learning across contexts

Proceedings of the National Academy of Sciences

Kasia Hitczenko

Naomi H Feldman

2022/9/20

A reinforcement learning approach to speech category acquisition

Proceedings of the Annual Boston University Conference on Language Development

Craig Thorburn

Ellen Lau

Naomi Feldman

2022/1

Modeling rhythm in speech as in music: Towards a unified cognitive representation

Proceedings of the Conference on Cognitive Computational Neuroscience

Ruolan Li

Thomas Schatz

Naomi H Feldman

2022/8

Making heads or tails of it: A competition–compensation account of morphological deficits in language impairment

Proceedings of the Annual Meeting of the Cognitive Science Society

Zara Harmon

Libby Barak

Patrick Shafto

Jan Edwards

Naomi H Feldman

2021

Do infants really learn phonetic categories?

Open Mind

Naomi H Feldman

Sharon Goldwater

Emmanuel Dupoux

Thomas Schatz

2021/11/1

Social inference may guide early lexical learning

Frontiers in Psychology

Alayo Tripp

Naomi H Feldman

William J Idsardi

2021/5/21

Japanese children’s knowledge of the locality of zibun and kare

Language Acquisition

Naho Orita

Hajime Ono

Naomi H Feldman

Jeffrey Lidz

2021/10/2

Informativity, topicality, and speech cost: comparing models of speakers’ choices of referring expressions

Discourse Processes

Naho Orita

Eliana Vornov

Naomi H Feldman

2021/9/14

Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input

Proceedings of the National Academy of Sciences

Thomas Schatz

Naomi H Feldman

Sharon Goldwater

Xuan-Nga Cao

Emmanuel Dupoux

2021/2/9

A phonetic model of non-native spoken word processing

arXiv preprint arXiv:2101.11332

Yevgen Matusevych

Herman Kamper

Thomas Schatz

Naomi H Feldman

Sharon Goldwater

2021/1/27

See List of Professors in Naomi Feldman University(University of Maryland, Baltimore)

Co-Authors

H-index: 110
Thomas L. Griffiths

Thomas L. Griffiths

Princeton University

H-index: 79
Emmanuel Dupoux

Emmanuel Dupoux

École des Hautes Études en Sciences Sociales

H-index: 50
Jordan Boyd-Graber

Jordan Boyd-Graber

University of Maryland, Baltimore

H-index: 47
Jeffrey Lidz

Jeffrey Lidz

University of Maryland, Baltimore

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