8 papers · 1 filter
From 2.1M Hours of Raw Broadcast Audio to Finnish Speech SSL: Confidence Filtering and Architectural Analysis at Scale
Yaroslav Getman, Tamás Grósz, Tommi Lehtonen +1
Broadcast archives offer scale and diversity for self-supervised learning (SSL) but contain substantial noisy, non-speech, and multilingual content. Prior work typically relies on…
A Native-Reference Phone-Class Geometry for Second-Language Pronunciation Analysis
Tina Raissi, Nhan Phan, Chenxiao Wang +1
Automatic speaking assessment systems can provide holistic proficiency scores, but often lack interpretable measures that characterize pronunciation quality. We propose a native-re…
A Native-Reference Coordinate Geometry for L2 Pronunciation Deviation Using Self-Supervised Speech Models
Tina Raissi, Nhan Phan, Mikko Kurimo
Self-supervised speech models encode rich phonetic information, but it remains unclear how to transform this information into interpretable metrics for second-language (L2) pronunc…
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.…
Multi-Teacher Language-Aware Knowledge Distillation for Multilingual Speech Emotion Recognition
Mehedi Hasan Bijoy, Dejan Porjazovski, Tamás Grósz +1
Speech Emotion Recognition (SER) is crucial for improving human-computer interaction. Despite strides in monolingual SER, extending them to build a multilingual system remains chal…
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…