5 papers · 1 filter
CASA: Content-Acoustic Speaking Assessment with Speech Encoder and Large Language Model
Nhan Phan, Ilona Lähteenmäki, Anna von Zansen +4
Research on automatic speaking assessment (ASA) has increasingly adopted multimodal speech large language models to assess learners' speaking performance. However, existing studies…
One Whisper to Grade Them All
Nhan Phan, Anusha Porwal, Yaroslav Getman +3
We present an efficient end-to-end approach for holistic Automatic Speaking Assessment (ASA) of multi-part second-language tests, developed for the 2025 Speak & Improve Challenge.…
Mispronunciation Detection Without L2 Pronunciation Dataset in Low-Resource Setting: A Case Study in Finland Swedish
Nhan Phan, Mikko Kuronen, Maria Kautonen +6
Mispronunciation detection (MD) models are the cornerstones of many language learning applications. Unfortunately, most systems are built for English and other major languages, whi…
Non-native Children's Automatic Speech Assessment Challenge (NOCASA)
Yaroslav Getman, Tamás Grósz, Mikko Kurimo +1
This paper presents the "Non-native Children's Automatic Speech Assessment" (NOCASA) - a data competition part of the IEEE MLSP 2025 conference. NOCASA challenges participants to d…
Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks
Anssi Moisio, Dejan Porjazovski, Aku Rouhe +5
The Donate Speech campaign has so far succeeded in gathering approximately 3600 hours of ordinary, colloquial Finnish speech into the Lahjoita puhetta (Donate Speech) corpus. The c…