Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Aleksandr Diment"'
Autor:
Bhiksha Raj, Toni Heittola, Emmanuel Vincent, Tuomas Virtanen, Benjamin Elizalde, Aleksandr Diment, Annamaria Mesaros
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing
IEEE/ACM Transactions on Audio, Speech and Language Processing
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2019, 27 (6), pp.992-1006. ⟨10.1109/TASLP.2019.2907016⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2019, 27 (6), pp.992-1006. ⟨10.1109/TASLP.2019.2907016⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2019, 27 (6), pp.992-1006. ⟨10.1109/TASLP.2019.2907016⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2019, 27 (6), pp.992-1006. ⟨10.1109/TASLP.2019.2907016⟩
Each edition of the challenge on Detection and Classification of Acoustic Scenes and Events (DCASE) contained several tasks involving sound event detection in different setups. DCASE 2017 presented participants with three such tasks, each having spec
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 26:281-295
In this paper we propose a method for separation of moving sound sources. The method is based on first tracking the sources and then estimation of source spectrograms using multichannel non-negative matrix factorization (NMF) and extracting the sourc
Publikováno v:
IJCNN
A machine learning method for the automatic detection of pronunciation errors made by non-native speakers of English is proposed. It consists of training word-specific binary classifiers on a collected dataset of isolated words with possible pronunci
Publikováno v:
Speech Communication. 76:157-169
A method for binaural rendering of sound scene recordings is proposed.Source signals and their direction of arrival is estimated using a microphone array.A low-rank NMF model for separation of sound sources is used.Speech intelligibility test with ov
Autor:
Aleksandr Diment, Tuomas Virtanen
Publikováno v:
WASPAA
Many machine learning tasks have been shown solvable with impressive levels of success given large amounts of training data and computational power. For the problems which lack data sufficient to achieve high performance, methods for transfer learnin
Autor:
Stefano Squartini, Tuomas Virtanen, Aleksandr Diment, Michele Valenti, Giambattista Parascandolo
Publikováno v:
IJCNN
This paper presents a novel application of convolutional neural networks (CNNs) for the task of acoustic scene classification (ASC). We here propose the use of a CNN trained to classify short sequences of audio, represented by their log-mel spectrogr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98cba9fa9df572ed113c6ea5ed1eebb8
https://trepo.tuni.fi/handle/10024/129205
https://trepo.tuni.fi/handle/10024/129205
Publikováno v:
EUSIPCO
Detection of whispered speech in the presence of high levels of background noise has applications in fraudulent behaviour recognition. For instance, it can serve as an indicator of possible insider trading. We propose a deep neural network (DNN)-base
Autor:
Tuomas Virtanen, Aleksandr Diment
Publikováno v:
WASPAA
This paper proposes dictionary learning with archetypes for audio processing. Archetypes refer to so-called pure types, which are a combination of a few data points and which can be combined to obtain a data point. The concept has been found useful i
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319129754
CMMR
CMMR
In this work, the feature based on the group delay function from all-pole models (APGD) is proposed for pitched musical instrument recognition. Conventionally, the spectrum-related features take into account merely the magnitude information, whereas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2027ad1a1137e2bf5ddb9bfdc0e48520
https://doi.org/10.1007/978-3-319-12976-1_37
https://doi.org/10.1007/978-3-319-12976-1_37
Publikováno v:
Tampere University
Publication in the conference proceedings of EUSIPCO, Marrakech, Morocco, 2013
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c62d9b607cba47eb051f5f766d5c64d7