Výsledky vyhledávání - "Pawel Swietojanski"

Akademický článek

Adaptation Algorithms for Neural Network-Based Speech Recognition: An Overview

Autor: Peter Bell, Joachim Fainberg, Ondrej Klejch, Jinyu Li, Steve Renals, Pawel Swietojanski

Publikováno v: IEEE Open Journal of Signal Processing, Vol 2, Pp 33-66 (2021)

We present a structured overview of adaptation algorithms for neural network-based speech recognition, considering both hybrid hidden Markov model / neural network systems and end-to-end neural network systems, with a focus on speaker adaptation, dom

Externí odkaz: https://doaj.org/article/051266d6d8f14251a11a9ac33b8a5a6c

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Automated Rock Quality Designation Using Convolutional Neural Networks

Autor: Fatimah Alzubaidi, Peyman Mostaghimi, Guangyao Si, Pawel Swietojanski, Ryan T. Armstrong

Publikováno v: Rock Mechanics and Rock Engineering. 55:3719-3734

Mineral and hydrocarbon exploration relies heavily on geological and geotechnical information extracted from drill cores. Traditional drill-core characterization is based purely on the subjective expertise of a geologist. New technologies can provide

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0f68945d2377a4f965d168d7fb15fd29
https://doi.org/10.1007/s00603-022-02805-y

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Adaptation Algorithms for Neural Network-Based Speech Recognition: An Overview

Autor: Jinyu Li, Peter Bell, Steve Renals, Pawel Swietojanski, Ondrej Klejch, Joachim Fainberg

Publikováno v: IEEE Open Journal of Signal Processing, Vol 2, Pp 33-66 (2021)
EEE Open Journal of Signal Processing
Bell, P, Fainberg, J, Klejch, O, Li, J, Renals, S & Swietojanski, P 2021, ' Adaptation Algorithms for Neural Network-Based Speech Recognition: An Overview ', IEEE Open Journal of Signal Processing, vol. 2, pp. 33-66 . https://doi.org/10.1109/OJSP.2020.3045349

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72964500baca881265b2151b66567c7e
https://ieeexplore.ieee.org/document/9296327/

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Benchmarking Natural Language Understanding Services for Building Conversational Agents

Autor: Pawel Swietojanski, Verena Rieser, Arash Eshghi, Xingkun Liu

Publikováno v: Lecture Notes in Electrical Engineering ISBN: 9789811593222
IWSDS

We have recently seen the emergence of several publicly available Natural Language Understanding (NLU) toolkits, which map user utterances to structured, but more abstract, Dialogue Act (DA) or Intent specifications, while making this process accessi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ae3a6b286f60ef19898c594834451b3a
https://doi.org/10.1007/978-981-15-9323-9_15

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An Innovative Application of Generative Adversarial Networks for Physically Accurate Rock Images With an Unprecedented Field of View

Autor: Ryan T. Armstrong, Peyman Mostaghimi, Ying Da Wang, Pawel Swietojanski, Yufu Niu

Publikováno v: Geophysical Research Letters. 47

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3b086738033b5a7ad5d3821f8f268d3e
https://doi.org/10.1029/2020gl089029

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SLURP: A Spoken Language Understanding Resource Package

Autor: Verena Rieser, Pawel Swietojanski, Emanuele Bastianelli, Andrea Vanzo

Publikováno v: EMNLP (1)

Spoken Language Understanding infers semantic meaning directly from audio data, and thus promises to reduce error propagation and misunderstandings in end-user applications. However, publicly available SLU resources are limited. In this paper, we rel

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c34122266405fac2c289693fac748729
http://arxiv.org/abs/2011.13205

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Digital Rock Segmentation for Petrophysical Analysis With Reduced User Bias Using Convolutional Neural Networks

Autor: Pawel Swietojanski, Mehdi Shabaninejad, Yufu Niu, Ryan T. Armstrong, Peyman Mostaghimi

Publikováno v: Water Resources Research. 56

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7ad6353bf65d908071b5fe0e8a588ab2
https://doi.org/10.1029/2019wr026597

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Multi-task self-supervised learning for Robust Speech Recognition

Autor: Santiago Pascual, Mirco Ravanelli, Jianyuan Zhong, Jan Trmal, Joao Monteiro, Pawel Swietojanski, Yoshua Bengio

Publikováno v: ICASSP

Despite the growing interest in unsupervised learning, extracting meaningful knowledge from unlabelled audio remains an open challenge. To take a step in this direction, we recently proposed a problem-agnostic speech encoder (PASE), that combines a c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99a19f66f756458a9da225e87dab1244
http://arxiv.org/abs/2001.09239

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Teacher-student Training for Acoustic Event Detection Using Audioset

Autor: Raymond W. M. Ng, Pawel Swietojanski, Ruibo Shi

Publikováno v: ICASSP

This paper studies Acoustic Event Detection (AED) systems and the problem of their rapid and easy customisation to arbitrary deployment scenarios. Due to inherent challenges related to annotation processes of AED data (time-consuming and error-prone

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4d45b57584b8cc58fbcf0e61ac43f6a9
https://doi.org/10.1109/icassp.2019.8683048

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Static Visual Spatial Priors for DoA Estimation

Autor: Ondrej Miksik, Pawel Swietojanski

Publikováno v: ICASSP

As we interact with the world, for example when we communicate with our colleagues in a large open space or meeting room, we continuously analyse the surrounding environment and, in particular, localise and recognise acoustic events. While we largely

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::346ae1c9133164736effe60e90d3e9e9

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