Nay San

Nay San

Stanford University

H-index: 4

North America-United States

About Nay San

Nay San, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at Stanford University, specializes in the field of phonology, Australian Aboriginal languages, lexicography, computational linguistics.

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

Predicting positive transfer for improved low-resource speech recognition using acoustic pseudo-tokens

Developing Speech Processing Pipelines for Police Accountability

Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation

Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions

The Kaytetye segmental inventory

Automated speech tools for helping communities process restricted-access corpora for language revival efforts

Managing Transcription Data for Automatic Speech Recognition with Elpis

Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages

Nay San Information

University

Position

___

Citations(all)

102

Citations(since 2020)

101

Cited By

34

hIndex(all)

4

hIndex(since 2020)

4

i10Index(all)

2

i10Index(since 2020)

2

Email

University Profile Page

Stanford University

Google Scholar

View Google Scholar Profile

Nay San Skills & Research Interests

phonology

Australian Aboriginal languages

lexicography

computational linguistics

Top articles of Nay San

Title

Journal

Author(s)

Publication Date

Predicting positive transfer for improved low-resource speech recognition using acoustic pseudo-tokens

Nay San

Georgios Paraskevopoulos

Aryaman Arora

Xiluo He

Prabhjot Kaur

...

2024/2/3

Developing Speech Processing Pipelines for Police Accountability

arXiv preprint arXiv:2306.06086

Anjalie Field

Prateek Verma

Nay San

Jennifer L Eberhardt

Dan Jurafsky

2023/6/9

Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation

arXiv preprint arXiv:2305.10951

Martijn Bartelds

Nay San

Bradley McDonnell

Dan Jurafsky

Martijn Wieling

2023/5/18

Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions

Nay San

Martijn Bartelds

Blaine Billings

Ella de Falco

Hendi Feriza

...

2023/2/9

The Kaytetye segmental inventory

Australian Journal of Linguistics

Mark Harvey

Nay San

Michael Proctor

Forrest Panther

Myfany Turpin

2023/1/2

Automated speech tools for helping communities process restricted-access corpora for language revival efforts

Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages

Nay San

Martijn Bartelds

Alison Mount

Ruben Thompson

Michael Higgins

...

2022/4/15

Managing Transcription Data for Automatic Speech Recognition with Elpis

The Open Handbook of Linguistic Data Management

Ben Foley

Daan van Esch

Nay San

2022/1/18

Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages

Nay San

Martijn Bartelds

Mitchell Browne

Lily Clifford

Fiona Gibson

...

2021/12/13

Text-setting in Kaytetye

Proceedings of the Annual Meetings on Phonology

Nay San

Myfany Turpin

2021/5/1

See List of Professors in Nay San University(Stanford University)