Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Ulpu Remes"'
Publikováno v:
Wellcome Open Research, Vol 4 (2019)
Likelihood-free inference for simulator-based models is an emerging methodological branch of statistics which has attracted considerable attention in applications across diverse fields such as population genetics, astronomy and economics. Recently, t
Externí odkaz:
https://doaj.org/article/2e59581b969d4c45a13e8945415f597e
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 25:1985-1996
Noise in the environment can decrease the quality and intelligibility of a telephone conversation. This study focuses on the intelligibility enhancement of narrowband telephone speech in a near-end noise scenario using a postprocessing method based o
Autor:
Kalle J. Palomäki, Lauri Juvela, Paavo Alku, Ana Ramírez López, Guy J. Brown, Mikko Kurimo, Ulpu Remes
Publikováno v:
Computer Speech & Language. 35:14-31
HighlightsMissing-data methods are evaluated in a perceptual restoration task.Human and automatic speech recognition performance are compared.Methods include a novel approach to cepstral-domain bounded marginalisation. Speech that has been distorted
Publikováno v:
Wellcome Open Research
Export Date: 10 February 2021 Correspondence Address: Kokko, J.; Department of Mathematics and Statistics, Finland; email: jan.kokko@helsinki.fi Likelihood-free inference for simulator-based models is an emerging methodological branch of statistics w
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 23(7):1198-1208
Automatic speech recognition systems use noise compensation and acoustic model adaptation to increase robustness towards speaker and environmental variation. The current work focuses on noise compensation with bounded conditional mean imputation (BCM
Publikováno v:
INTERSPEECH
Zero-resource speech processing (ZS) systems aim to learn structural representations of speech without access to labeled data. A starting point for these systems is the extraction of syllable tokens utilizing the rhythmic structure of a speech signal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0fff45c03d5074abe5bbac6b61932f5
http://hdl.handle.net/10138/231768
http://hdl.handle.net/10138/231768
Publikováno v:
ICASSP
Non-parametric Bayesian methods have recently gained popularity in several research areas dealing with unsupervised learning. These models are capable of simultaneously learning the cluster models as well as their number based on properties of a data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b851c2a37fe4b1b9bbcb58803cb3c53e
https://doi.org/10.1109/ICASSP.2017.7953202
https://doi.org/10.1109/ICASSP.2017.7953202
Publikováno v:
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING. 8(2):285-295
This work describes experiments on using noisy adaptation data to create personalized voices with HMM-based speech synthesis. We investigate how environmental noise affects feature extraction and CSMAPLR and EMLLR adaptation. We investigate effects o
Publikováno v:
INTERSPEECH
Publikováno v:
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING. 20(8):2219-2231
The quality of narrowband telephone speech is degraded by the limited audio bandwidth. This paper describes a method that extends the bandwidth of telephone speech to the frequency range 0-300 Hz. The method generates the lowest harmonics of voiced s