SAIT-EMA: A Tridimensional Electromagnetic Articulography Database for Mandarin with Diverse Language Backgrounds

Electromagnetic Articulography (EMA), an instrument to capture high-precision 3D movement data of the tongue, lips, and jaw, has been widely employed in speech production research, L2 instruction, and clinical rehabilitation. This study introduces the SAIT-EMA database, a Mandarin speech corpus that integrates articulatory and acoustic data from both native speakers of Mandarin and second language learners from diverse first-language backgrounds. The database comprises data from 18 participants (9 male and 9 female), including six L2 learners from Vietnam, Peru, Mexico, and Russia, and twelve native Mandarin speakers as a control group (two highly proficient speakers and ten general native speakers). Data were collected using the Carstens AG501 EMA system, with nine sensors attached to articulators: tongue tip (TT), tongue blade (TB), tongue dorsum (TD), lower incisors (LI), upper lip (UL), lower lip (LL), nasal bridge (NR), and bilateral mastoids (LE and RE). Articulatory data were sampled at 250 Hz, with synchronized audio recorded at 48 kHz, resulting in motion data in.pos format and standard.wav audio files. The speech materials were selected from a Mandarin interlanguage speech corpus, covering a broad range of phonetic phenomena including segments, tones, tone sandhi, and focus prosody-ensuring coverage of key issues in L2 phonetic research. The SAIT-EMA database offers the resource specifically targeting articulatory patterns in Mandarin L2 learners from diverse language backgrounds. It provides a valuable foundation for testing theoretical hypotheses in L2 acquisition and supports the development of intelligent computer aided pronunciation training technologies.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2026-04-22
DOI
https://doi.org/10.1038/s41597-026-07237-9
Primary Topic
Phonetics and Phonology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SAIT-EMA: A Tridimensional Electromagnetic Articulography Database for Mandarin with Diverse Language Backgrounds

Yanlu Xie, Yifeng Sun, Qiang Fang, Hui Jia
Scientific Data
Phonetics and Phonology Research
article

SAIT-EMA: A Tridimensional Electromagnetic Articulography Database for Mandarin with Diverse Language Backgrounds

Yanlu Xie, Yifeng Sun, Qiang Fang, Hui Jia
article en

Abstract

Electromagnetic Articulography (EMA), an instrument to capture high-precision 3D movement data of the tongue, lips, and jaw, has been widely employed in speech production research, L2 instruction, and clinical rehabilitation. This study introduces the SAIT-EMA database, a Mandarin speech corpus that integrates articulatory and acoustic data from both native speakers of Mandarin and second language learners from diverse first-language backgrounds. The database comprises data from 18 participants (9 male and 9 female), including six L2 learners from Vietnam, Peru, Mexico, and Russia, and twelve native Mandarin speakers as a control group (two highly proficient speakers and ten general native speakers). Data were collected using the Carstens AG501 EMA system, with nine sensors attached to articulators: tongue tip (TT), tongue blade (TB), tongue dorsum (TD), lower incisors (LI), upper lip (UL), lower lip (LL), nasal bridge (NR), and bilateral mastoids (LE and RE). Articulatory data were sampled at 250 Hz, with synchronized audio recorded at 48 kHz, resulting in motion data in.pos format and standard.wav audio files. The speech materials were selected from a Mandarin interlanguage speech corpus, covering a broad range of phonetic phenomena including segments, tones, tone sandhi, and focus prosody-ensuring coverage of key issues in L2 phonetic research. The SAIT-EMA database offers the resource specifically targeting articulatory patterns in Mandarin L2 learners from diverse language backgrounds. It provides a valuable foundation for testing theoretical hypotheses in L2 acquisition and supports the development of intelligent computer aided pronunciation training technologies.

Scientific Data
Chinese Academy of Social Sciences (CN), Beijing Language and Culture University (CN)
Quality Education
Openalex Percentile: Top 12%
Phonetics and Phonology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.