Bożena Kostek - Publications - Bridge of Knowledge

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Year 2022
Year 2021
  • Acoustic Sensing Analytics Applied to Speech in Reverberation Conditions
    Publication

    The paper aims to discuss a case study of sensing analytics and technology in acoustics when applied to reverberation conditions. Reverberation is one of the issues that makes speech in indoor spaces challenging to understand. This problem is particularly critical in large spaces with few absorbing or diffusing surfaces. One of the natural remedies to improve speech intelligibility in such conditions may be achieved through speaking...

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  • AUTOMATYCZNE GENEROWANIE KOLEJNOŚCI LIST UTWORÓW MUZYCZNYCH
    Publication

    - Year 2021

    W niniejszym rozdziale przedstawiono przygotowanie algorytmu do automa-tycznego układania kolejności utworów muzycznych i zgrywającego je do postaci jednego, długiego miksu. Dzięki algorytmowi dobierane są utwory na podstawie analizy podobieństwa fragmentów końcowych i początkowych utworów. Podo-bieństwo to jest obliczane za pomocą odległości euklidesowej między wektorami parametrów wyznaczonymi przez autoenkoder oraz na podstawie...

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  • Classifying Emotions in Film Music - A Deep Learning Approach

    The paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...

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  • Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
    Publication

    - Year 2021

    This paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...

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  • Evaluation of aspiration problems in L2 English pronunciation employing machine learning

    The approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...

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  • Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
    Publication

    - Journal of the Acoustical Society of America - Year 2021

    The goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...

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  • How Machine Learning Contributes to Solve Acoustical Problems
    Publication
    • M. A. Roch
    • P. Gerstoft
    • B. Kostek
    • Z. Michalopoulou

    - Journal of the Acoustical Society of America - Year 2021

    Machine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...

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  • Introduction to the special issue on machine learning in acoustics
    Publication
    • Z. Michalopoulou
    • P. Gerstoft
    • B. Kostek
    • M. A. Roch

    - Journal of the Acoustical Society of America - Year 2021

    When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...

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  • KLASYFIKACJA EMOCJI W MUZYCE FILMOWEJ Z WYKORZYSTANIEM TESTÓW SUBIEKTYWNYCH

    Celem referatu było przedstawienie testów odsłuchowych, w których zadaniem osób ankietowanych było przypisanie danego fragmentu muzycznego do odpowiedniej klasy emocji. Kolejne kroki eksperymentu obejmowały wybór muzyki filmowej do testów (baza Epidemic Sound), przygotowanie założeń ankiety oraz modelu emocji wykorzystywanych w testach odsłuchowych, jak również konstrukcj ˛e ankiety. Ankieta została zrealizowana za pomoc ˛a formularzy...

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