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Wyniki wyszukiwania dla: SPEECH SIGNAL
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Tensor Decomposition for Imagined Speech Discrimination in EEG
PublikacjaMost of the researches in Electroencephalogram(EEG)-based Brain-Computer Interfaces (BCI) are focused on the use of motor imagery. As an attempt to improve the control of these interfaces, the use of language instead of movement has been recently explored, in the form of imagined speech. This work aims for the discrimination of imagined words in electroencephalogram signals. For this purpose, the analysis of multiple variables...
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublikacjaIn 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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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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A study on signal processing methods applied to hearing aids
PublikacjaThis paper presents a short survey on current technology available in hearing aids with a focus on digital signal processing techniques used. First, factors influencing the hearing aid effectiveness are introduced. Then, examples of the present DSP methods and strategies are provided. Also, a description of current limitations of hearing aids and future trends of development are shown. Finally, the notion of computational auditory...
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Instantaneous complex frequency for pipeline pitch estimation
PublikacjaIn the paper a pipeline algorithm for estimating the pitch of speech signal is proposed. The algorithm uses instantaneous complex frequencies estimated for four waveforms obtained by filtering the original speech signal through four bandpass complex Hilbert filters. The imaginary parts of ICFs from each channel give four candidates for pitch estimates. The decision regarding the final estimate is made based on the real parts of...
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Weakly-Supervised Word-Level Pronunciation Error Detection in Non-Native English Speech
PublikacjaWe 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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Metoda i algorytmy modyfikacji sygnału do celu wspomagania rozumienia mowy przez osoby z pogorszoną rozdzielczością czasową słuchu
PublikacjaPrzedmiotem badań przeprowadzonych w ramach rozprawy są metody modyfikacji czasu trwania sygnału (ang. Time Scale Modification –TSM) mowy operujące w czasie rzeczywistym oraz ocena ich wpływu na rozumienie wypowiedzi przez osoby z pogorszoną rozdzielczością czasową słuchu. Pogorszona rozdzielczość słuchu jest jednym z symptomów związanych z ośrodkowymi zaburzeniami słuchu (ang. Cetnral Auditory Processing Disorder – CAPD). W odróżnieniu...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublikacjaThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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Human voice modification using instantaneous complex frequency
PublikacjaThe paper presents the possibilities of changing human voice by modifying instantaneous complex frequency (ICF) of the speech signal. The proposed method provides a flexible way of altering voice without the necessity of finding fundamental frequency and formants' positions or detecting voiced and unvoiced fragments of speech. The algorithm is simple and fast. Apart from ICF it uses signal factorization into two factors: one fully...
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AUTOMATYCZNA KLASYFIKACJA MOWY PATOLOGICZNEJ
PublikacjaAplikacja 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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Audio-visual aspect of the Lombard effect and comparison with recordings depicting emotional states.
PublikacjaIn this paper an analysis of audio-visual recordings of the Lombard effect is shown. First, audio signal is analyzed indicating the presence of this phenomenon in the recorded sessions. The principal aim, however, was to discuss problems related to extracting differences caused by the Lombard effect, present in the video , i.e. visible as tension and work of facial muscles aligned to an increase in the intensity of the articulated...
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A low complexity double-talk detector based on the signal envelope
PublikacjaA new algorithm for double-talk detection, intended for use in the acoustic echo canceller for voice communication applications, is proposed. The communication system developed by the authors required the use of a double-talk detection algorithm with low complexity and good accuracy. The authors propose an approach to doubletalk detection based on the signal envelopes. For each of three signals: the far-end speech, the microphone...
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Marking the Allophones Boundaries Based on the DTW Algorithm
PublikacjaThe paper presents an approach to marking the boundaries of allophones in the speech signal based on the Dynamic Time Warping (DTW) algorithm. Setting and marking of allophones boundaries in continuous speech is a difficult issue due to the mutual influence of adjacent phonemes on each other. It is this neighborhood on the one hand that creates variants of phonemes that is allophones, and on the other hand it affects that the border...
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Enhanced voice user interface employing spatial filtration of signals from acoustic vector sensor
PublikacjaSpatial filtration of sound is introduced to enhance speech recognition accuracy in noisy conditions. An acoustic vector sensor (AVS) is employed. The signals from the AVS probe are processed in order to attenuate the surrounding noise. As a result the signal to noise ratio is increased. An experiment is featured in which speech signals are disturbed by babble noise. The signals before and after spatial filtration are processed...
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Quality Evaluation of Speech Transmission via Two-way BPL-PLC Voice Communication System in an Underground Mine
PublikacjaIn order to design a stable and reliable voice communication system, it is essential to know how many resources are necessary for conveying quality content. These parameters may include objective quality of service (QoS) metrics, such as: available bandwidth, bit error rate (BER), delay, latency as well as subjective quality of experience (QoE) related to user expectations. QoE is expressed as clarity of speech and the ability...
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Analysis of allophones based on audio signal recordings and parameterization
PublikacjaThe aim of this study is to develop an allophonic description of English plosive consonants based on recordings of 600 specially selected words. Allophonic variations addressed in the study may have two sources: positional and contextual. The former one depends on the syllabic or prosodic position in which a particular phoneme occurs. Contextual allophony is conditioned by the local phonetic environment. Co-articulation overlapping...
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Estimation of time-frequency complex phase-based speech attributes using narrow band filter banks
PublikacjaIn this paper, we present nonlinear estimators of nonstationary and multicomponent signal attributes (parameters, properties) which are instantaneous frequency, spectral (or group) delay, and chirp-rate (also known as instantaneous frequency slope). We estimate all of these distributions in the time-frequency domain using both finite and infinite impulse response (FIR and IIR) narrow band filers for speech analysis. Then, we present...
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Strategie treningu neuronowego estymatora częstotliwości tonu krtaniowego z użyciem generatora syntetycznych samogłosek
PublikacjaW wielu zastosowaniach telekomunikacyjnych pojawia się problem przetwarzania lub analizy sygnału mowy, w ramach którego, często w obszarze podstawowych algorytmów, stosuje się estymator częstotliwości tonu krtaniowego. Estymator rozpatrywany w tej pracy bazuje na neuronowym klasyfikatorze podejmującym decyzje na podstawie częstotliwości oraz mocy chwilowej wyznaczanych w podpasmach analizowanego sygnału mowy. W pracy rozważamy...
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...