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FROST-EMA: Finnish and Russian Oral Speech Dataset of Electromagnetic Articulography Measurements with L1, L2 and Imitated L2 Accents

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arxiv 2506.08981 v1 pith:MOR44XVF submitted 2025-06-10 cs.CL

FROST-EMA: Finnish and Russian Oral Speech Dataset of Electromagnetic Articulography Measurements with L1, L2 and Imitated L2 Accents

Satu Hopponen , Tomi Kinnunen , Alexandre Nikolaev , Rosa Gonz\'alez Hautam\"aki , Lauri Tavi , Einar Meister This is my paper
classification cs.CL
keywords imitatedlanguagespeechaccentarticulographycasecorpusdataset
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We introduce a new FROST-EMA (Finnish and Russian Oral Speech Dataset of Electromagnetic Articulography) corpus. It consists of 18 bilingual speakers, who produced speech in their native language (L1), second language (L2), and imitated L2 (fake foreign accent). The new corpus enables research into language variability from phonetic and technological points of view. Accordingly, we include two preliminary case studies to demonstrate both perspectives. The first case study explores the impact of L2 and imitated L2 on the performance of an automatic speaker verification system, while the second illustrates the articulatory patterns of one speaker in L1, L2, and a fake accent.

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  1. Beyond Speaker Independence: Evaluating Cross-Lingual Acoustic-to-Articulatory Inversion Across Finnish and Russian

    eess.AS 2026-06 unverdicted novelty 4.0

    Benchmarks on the new FROST-EMA corpus show cross-language mismatch drops Pearson correlation by 0.10-0.20 while cross-gender mismatch drops it by 0.05-0.10.