Zobrazeno 1 - 10 of 61 pro vyhledávání: '"Torbjørn Svendsen"'
3
wav2vec2-based Speech Rating System for Children with Speech Sound Disorder
Autor: Yaroslav Getman, Ragheb Al-Ghezi, Katja Voskoboinik, Tamás Grósz, Mikko Kurimo, Giampiero Salvi, Torbjørn Svendsen, Sofia Strömbergsson
Publikováno v: Interspeech 2022.
Speaking is a fundamental way of communication, developed at a young age. Unfortunately, some children with speech sound disorder struggle to acquire this skill, hindering their ability to communicate efficiently. Speech therapies, which could aid th
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3753090564cf4d8a9e877883b5711da4
https://doi.org/10.21437/interspeech.2022-10103
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4
On the Predictive Power of Objective Intelligibility Metrics for the Subjective Performance of Deep Complex Convolutional Recurrent Speech Enhancement Networks
Autor: Tor Andre Myrvoll, Torbjørn Svendsen, Tron V. Tronstad, Femke B. Gelderblom
Speech enhancement (SE) systems aim to improve the quality and intelligibility of degraded speech signals obtained from far-field microphones. Subjective evaluation of the intelligibility performance of these SE systems is uncommon. Instead, objectiv
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::465b85ed58ab0c311c48513cbaf3ab2a
https://doi.org/10.36227/techrxiv.19698502
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5
Semantically Meaningful Metrics for Norwegian ASR Systems
Autor: Janine Rugayan, Torbjørn Svendsen, Giampiero Salvi
Publikováno v: Interspeech (USB)
Evaluation metrics are important for quanitfying the performance of Automatic Speech Recognition (ASR) systems. However, the widely used word error rate (WER) captures errors at the word-level only and weighs each error equally, which makes it insuff
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f872b264b20577a849733b9a0777338
https://hdl.handle.net/11250/3051822
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7
A DNN Based Speech Enhancement Approach to Noise Robust Acoustic-to-Articulatory Inversion
Autor: Sabato Marco Siniscalchi, Torbjørn Svendsen, Abdolreza Sabzi Shahrebabaki, Giampiero Salvi
Publikováno v: ISCAS
In this work, we investigate the problem of speaker independent acoustic-to-articulatory inversion (AAI) in noisy condition within the deep neural network (DNN) framework. We claim that DNN vector-to-vector regression for speech enhancement (DNN-SE)
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91632a7ee6c396afe93e0e4c92e9fe41
https://hdl.handle.net/11250/3025915
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9
Transfer learning of articulatory information through phone information
Autor: Sabato Marco Siniscalchi, Abdolreza Sabzi Shahrebabaki, Giampiero Salvi, Torbjørn Svendsen, Negar Olfati
Publikováno v: Interspeech
INTERSPEECH
Articulatory information has been argued to be useful for several speech tasks. However, in most practical scenarios this information is not readily available. We propose a novel transfer learning framework to obtain reliable articulatory information
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5017a0bbad2131d52109efe4374ab8e
https://hdl.handle.net/11250/2740290
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10
Text-Independent Speaker ID Employing 2D-CNN for Automatic Video Lecture Categorization in a MOOC Setting
Autor: Torbjørn Svendsen, Arianit Kurti, Zenun Kastrati, Ali Shariq Imran
Publikováno v: ICTAI
A new form of distance and blended education has hit the market in recent years with the advent of massive open online courses (MOOCs) which have brought many opportunities to the educational sector. Consequently, the availability of learning content
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e1c36e074fa3abaf7a23c54d6dca89a6
https://doi.org/10.1109/ictai.2019.00046
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