activity
20222026
most citedAdvancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference

5 citations · 5 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

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.…

cs.CL2025

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…

cs.CL2025

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…

eess.AS2023★ 5 cited

Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference

Dejan Porjazovski, Yaroslav Getman, Tamás Grósz +1

Large pre-trained models are essential in paralinguistic systems, demonstrating effectiveness in tasks like emotion recognition and stuttering detection. In this paper, we employ l…

cs.CL2022

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…