A Tunable Forced Alignment System Based on Deep Learning: Applications to Child Speech

Authors

Prad Kadambi
Katherine C. Hustad (ORCID: https://orcid.org/0000-0002-8544-7754)
Visar Berisha (ORCID: https://orcid.org/0000-0001-8804-8874)
Tristan Mahr (ORCID: https://orcid.org/0000-0002-8890-5116)

Institutions

University of Wisconsin–Madison (US)
Arizona State University (US)

Publication Details

Journal: Journal of Speech Language and Hearing Research
Published: 2025-03-31
DOI: https://doi.org/10.1044/2024_jslhr-24-00347
Primary Topic: Speech Recognition and Synthesis
Type: article
Field-Weighted Citation Impact: 0.00

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article

A Tunable Forced Alignment System Based on Deep Learning: Applications to Child Speech

Prad Kadambi, Katherine C. Hustad, Visar Berisha, Tristan Mahr

Mar 31, 2025

Journal of Speech Language and Hearing Research

Speech Recognition and Synthesis

article

A Tunable Forced Alignment System Based on Deep Learning: Applications to Child Speech

Prad Kadambi, Katherine C. Hustad, Visar Berisha, Tristan Mahr

March 31, 2025article en

Abstract

No abstract available for this paper.

Journal of Speech Language and Hearing ResearchVol. 68(7S)

University of Wisconsin–Madison (US), Arizona State University (US)

Peace, Justice and strong institutions

Openalex Percentile: Top 97%

Speech Recognition and Synthesis

DOI Open Access PDF OpenAlex

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A Tunable Forced Alignment System Based on Deep Learning: Applications to Child Speech — Prad Kadambi, Katherine C. Hustad, et al. · Journal of Speech Language and Hearing Research (2025) | TGRS Research Map | TGRS