Third-person overt pronoun and zero reference in Estonian. Insights from two experiments

Autor: Helen Hint, Maria Reile, Elsi Kaiser

Publikováno v: Eesti ja Soome-ugri Keeleteaduse Ajakiri, Vol 14, Iss 2 (2023)

This study reports two experiments that investigate the variation between two Estonian third-person referential devices – zero reference vs. the overt pronoun ta. First, in a speech-restoration paradigm (Experiment 1), we test whether the structure

Externí odkaz: https://doaj.org/article/25a35975fa864246ac305a4858c92791

Speech enhancement by LSTM-based noise suppression followed by CNN-based speech restoration

Autor: Maximilian Strake, Bruno Defraene, Kristoff Fluyt, Wouter Tirry, Tim Fingscheidt

Publikováno v: EURASIP Journal on Advances in Signal Processing, Vol 2020, Iss 1, Pp 1-26 (2020)

Abstract Single-channel speech enhancement in highly non-stationary noise conditions is a very challenging task, especially when interfering speech is included in the noise. Deep learning-based approaches have notably improved the performance of spee

Externí odkaz: https://doaj.org/article/565f8fc0d3a94182b4106ab639dfc73d

Prosthetic voice rehabilitation after laryngoesophagectomy: surgical and functional outcomes

Autor: Gabriele Molteni, Gianfranco Fulco, Luca Gazzini, Elisa Laura, Giuliana Paiola, Simone Giacopuzzi, Daniele Marchioni, Gian Paolo Pighi

Publikováno v: European Archives of Oto-Rhino-Laryngology. 279:4085-4092

Quality of Life (QoL) after extensive head and neck resections is of paramount importance, especially after pharyngolaryngectomy or pharyngolaryngoesophagectomy where complex digestive tract reconstruction is required (with gastric pull-up or colon t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63612719f6aa0ca5ce014d972cae16ad
https://doi.org/10.1007/s00405-022-07251-8

Speech enhancement by LSTM-based noise suppression followed by CNN-based speech restoration

Autor: Bruno Defraene, Tim Fingscheidt, Wouter Tirry, Maximilian Strake, Kristoff Fluyt

Publikováno v: EURASIP Journal on Advances in Signal Processing, Vol 2020, Iss 1, Pp 1-26 (2020)
EURASIP Journal on Advances in Signal Processing, 2020, 49 (2020). https://doi.org/10.1186/s13634-020-00707-1--http://asp.eurasipjournals.com/--http://www.bibliothek.uni-regensburg.de/ezeit/?2364203--1687-6180

Single-channel speech enhancement in highly non-stationary noise conditions is a very challenging task, especially when interfering speech is included in the noise. Deep learning-based approaches have notably improved the performance of speech enhanc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e7a3be4309dc4a2b535f94890c37812
https://doaj.org/article/565f8fc0d3a94182b4106ab639dfc73d

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