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Year 2023
  • Applying the Lombard Effect to Speech-in-Noise Communication
    Publication

    - Electronics - Year 2023

    This study explored how the Lombard effect, a natural or artificial increase in speech loudness in noisy environments, can improve speech-in-noise communication. This study consisted of several experiments that measured the impact of different types of noise on synthesizing the Lombard effect. The main steps were as follows: first, a dataset of speech samples with and without the Lombard effect was collected in a controlled setting;...

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  • Assessing the attractiveness of human face based on machine learning
    Publication

    The attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...

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  • Automatic music signal mixing system based on one-dimensional Wave-U-Net autoencoders
    Publication

    The purpose of this paper is to show a music mixing system that is capable of automatically mixing separate raw recordings with good quality regardless of the music genre. This work recalls selected methods for automatic audio mixing first. Then, a novel deep model based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. The model is trained on a custom-prepared database. Mixes created using the...

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  • AUTOMATYCZNA KLASYFIKACJA MOWY PATOLOGICZNEJ
    Publication

    Aplikacja przedstawiona w niniejszym rozdziale służy do automatycznego wykrywania mowy patologicznej na podstawie bazy nagrań. W pierwszej kolejności przedstawiono założenia leżące u podstaw przeprowadzonych badan wraz z wyborem bazy mowy patologicznej. Zaprezentowano również zastosowane algorytmy oraz cechy sygnału mowy, które pozwalają odróżnić mowę niezaburzoną od mowy patologicznej. Wytrenowane sieci neuronowe zostały następnie...

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  • Combining MUSHRA Test and Fuzzy Logic in the Evaluation of Benefits of Using Hearing Prostheses
    Publication

    - Electronics - Year 2023

    Assessing the effectiveness of hearing aid fittings based on the benefits they provide is crucial but intricate. While objective metrics of hearing aids like gain, frequency response, and distortion are measurable, they do not directly indicate user benefits. Hearing aid performance assessment encompasses various aspects, such as compensating for hearing loss and user satisfaction. The authors suggest enhancing the widely used...

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  • Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
    Publication

    - Year 2023

    In this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....

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  • Detecting Lombard Speech Using Deep Learning Approach
    Publication
    • K. Kąkol
    • G. Korvel
    • G. Tamulevicius
    • B. Kostek

    - SENSORS - Year 2023

    Robust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...

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  • INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
    Publication

    The Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...

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  • Klasyfikacja emocji w muzyce filmowej z wykorzystaniem uczenia głębokiego
    Publication

    - Year 2023

    Praca przedstawia zagadnienia związane z klasyfikacją emocji w muzyce filmowej. W artykule zaproponowano model emocji zawierający dziewięć stanów emocjonalnych, do których przypisany jest kolor zgodnie z teorią koloru w filmie. Kolejne kroki eksperymentu obejmowały wybór muzyki filmowej do testów (baza Epidemic Sound), przygotowanie założeń ankiety oraz modelu emocji wykorzystywanych w testach odsłuchowych, a także konstrukcję...

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  • Predicting emotion from color present in images and video excerpts by machine learning
    Publication

    This work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...

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  • Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
    Publication

    - Applied Sciences-Basel - Year 2023

    This work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...

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  • SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM

    The main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...

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  • WYKORZYSTANIE TESTU MUSHRA W BADANIU KORZYŚCI UŻYTKOWANIA PROTEZ SŁUCHOWYCH
    Publication

    - Year 2023

    Ocena jakości dopasowania aparatów słuchowych w kontekście korzyści, jakie może przy-nieść proteza jest złożonym zagadnieniem. Obiektywne parametry aparatów, które można wy-znaczyć (np. wzmocnienie czy pasmo przenoszenia) nie zawsze mają bezpośredni i decydujący wpływ w subiektywnej ocenie jakości dopasowania protezy słuchowej przez pacjenta. Pomiary efektywności aparatu słuchowego mogą dotyczyć wielu aspektów, między innymi kompensacji...

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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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  • Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling
    Publication

    - Year 2021

    A common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...

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  • Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
    Publication

    The aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...

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  • Skuteczność klasyfikacji gatunków muzycznych za pomocą sieci neuronowej w zależności od typu danych wejściowych
    Publication

    Rozpoznawanie gatunku muzycznego jest jednym z podstawowych elementów inteligentnych systemów tworzenia automatycznych list muzyki. Platformy strumieniowe oferujące taką usługę wymagają rozwiązań, które umożliwią jak najdokładniej określić przynależność utworu do gatunku muzycznego. Zgodnie z aktualnym stanem wiedzy – najskuteczniejszym klasyfikatorem są sztuczne sieci neuronowe (w tym w wersji uczenia głębokiego), dla których...

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  • Techniki wielokanałowe wykorzystywane w koncertach i nagraniach muzycznych na odległość
    Publication

    - Year 2021

    W czasie pandemii koronawirusa COVID-19 nowego znaczenia nabrały możliwości transmisji dźwięku z obrazem – zwłaszcza do pracy zdalnej, która w przypadku muzyków jest szczególnym wyzwaniem zarówno w kontekście wspólnych ćwiczeń i prób, jak i koncertów. Wynikła konieczność wieloźródłowego połączenia ujawniła potrzebę uprzestrzennienia dźwięku w celu łatwiejszej lokalizacji źródeł dźwięku. Tworzenie zdalnych nagrań muzycznych stało...

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  • Weakly-Supervised Word-Level Pronunciation Error Detection in Non-Native English Speech
    Publication
    • D. Korzekwa
    • J. Lorenzo-trueba
    • T. Drugman
    • S. Calamaro
    • B. Kostek

    - Year 2021

    We propose a weakly-supervised model for word-level mispronunciation detection in non-native (L2) English speech. To train this model, phonetically transcribed L2 speech is not required and we only need to mark mispronounced words. The lack of phonetic transcriptions for L2 speech means that the model has to learn only from a weak signal of word-level mispronunciations. Because of that and due to the limited amount of mispronounced...

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Year 2020
  • A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
    Publication
    • G. Tamulevicius
    • G. Korvel
    • A. B. Yayak
    • P. Treigys
    • J. Bernataviciene
    • B. Kostek

    - Electronics - Year 2020

    In this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...

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  • Analiza ruchu drogowego z wykorzystaniem analizy akustycznej

    Tematyka pracy porusza zagadnienia dotyczące pozyskiwania informacji o ruchu drogowym z wykorzystaniem monitoringu akustycznego. Przybliżono podstawowe techniki nadzoru nad ruchem drogowym. Przedstawiono założenia akustycznego detektora ruchu i zbadano jego skuteczność na trzech płaszczyznach działania – zliczania pojazdów, klasyfikacji rodzajowej i klasyfikacji warunków pogodowych panujących na nawierzchni

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  • Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
    Publication

    The aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...

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  • Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
    Publication

    The purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....

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  • Evaluation of Lombard Speech Models in the Context of Speech in Noise Enhancement
    Publication

    - IEEE Access - Year 2020

    The Lombard effect is one of the most well-known effects of noise on speech production. Speech with the Lombard effect is more easily recognizable in noisy environments than normal natural speech. Our previous investigations showed that speech synthesis models might retain Lombard-effect characteristics. In this study, we investigate several speech models, such as harmonic, source-filter, and sinusoidal, applied to Lombard speech...

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  • Improving Objective Speech Quality Indicators in Noise Conditions
    Publication

    - Year 2020

    This work aims at modifying speech signal samples and test them with objective speech quality indicators after mixing the original signals with noise or with an interfering signal. Modifications that are applied to the signal are related to the Lombard speech characteristics, i.e., pitch shifting, utterance duration changes, vocal tract scaling, manipulation of formants. A set of words and sentences in Polish, recorded in silence,...

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