Browsing by Author "Kallio, Heini"

Filter results by typing the first few letters
Now showing 1 - 4 of 4
  • Automatic Speaking Assessment of Spontaneous L2 Finnish and Swedish
    (2023) Al-Ghezi, Ragheb; Voskoboinik, Ekaterina; Getman, Yaroslav; Von Zansen, Anna; Kallio, Heini; Kurimo, Mikko; Huhta, Ari; Hildén, Raili
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The development of automated systems for evaluating spontaneous speech is desirable for L2 learning, as it can be used as a facilitating tool for self-regulated learning, language proficiency assessment, and teacher training programs. However, languages with fewer learners face challenges due to the scarcity of training data. Recent advancements in machine learning have made it possible to develop systems with a limited amount of target domain data. To this end, we propose automatic speaking assessment systems for spontaneous L2 speech in Finnish and Finland Swedish, comprising six machine learning models each, and report their performance in terms of statistical evaluation criteria.
  • Digitala: An augmented test and review process prototype for high-stakes spoken foreign language examination
    (2016) Karhila, Reima; Rouhe, Aku; Smit, Peter; Mansikkaniemi, André; Kallio, Heini; Lindroos, Erik; Hildén, Raili; Vainio, Martti; Kurimo, Mikko
     A4 Artikkeli konferenssijulkaisussa
    This paper introduces the first prototype for a computerised examination procedure of spoken foreign languages in Finland, intended for national scale upper secondary school final examinations. Speech technology and profiling of reviewers are used to minimise the otherwise massive reviewing effort.
  • New data, benchmark and baseline for L2 speaking assessment for low-resource languages
    (2023) Kurimo, Mikko; Getman, Yaroslav; Voskoboinik, Ekaterina; Al-Ghezi, Ragheb; Kallio, Heini; Kuronen, Mikko; von Zansen, Anna; Hilden, Raili; Kronholm, Sirkku; Huhta, Ari; Lindén, Krister
     A4 Artikkeli konferenssijulkaisussa
    The development of large multilingual speech models provides the possibility to construct high-quality speech technology even for low-resource languages. In this paper, we present the speech data of L2 learners of Finnish and Finland Swedish that we have recently collected for training and evaluation of automatic speech recognition (ASR) and speaking assessment (ASA). It includes over 4000 recordings by over 300 students per language in short read-aloud and free-form tasks. The recordings have been manually transcribed and assessed for pronunciation, fluency, range, accuracy, task achievement, and a holistic proficiency level. We present also an ASR and ASA benchmarking setup we have constructed using this data and include results from our baseline systems built by fine-tuning self-supervised multilingual model for the target language. In addition to benchmarking, our baseline system can be used by L2 students and teachers for online self-training and evaluation of oral proficiency.
  • SIAK — A Game for Foreign Language Pronunciation Learning
    (2017-08) Karhila, Reima; Ylinen, Sari; Enarvi, Seppo; Palomäki, Kalle; Nikulin, Aleksander; Rantula, Olli; Viitanen, Vertti; Dhinakaran, Krupakar; Smolander, Anna-Riikka; Kallio, Heini; Junttila, Katja; Uther, Maria; Hämäläinen, Perttu; Kurimo, Mikko
     A4 Artikkeli konferenssijulkaisussa
    We introduce a digital game for children’s foreign-language learning that uses automatic speech recognition (ASR) for evaluating children’s utterances. Our first prototype focuses on the learning of English words and their pronunciation. The game connects to a network server, which handles the recognition and pronunciation grading of children’s foreign-language speech. The server is reusable for different applications. Given suitable acoustic models, it can be used for grading pronunciations in any language.