Zobrazeno 1 - 10
of 841
pro vyhledávání: '"T. Toledano"'
Publikováno v:
Nuclear Engineering and Technology, Vol 56, Iss 10, Pp 4062-4067 (2024)
In this article, we propose and explore a novel step in the digitization of the mapping of the spent fuel pool of nuclear power plants, in which the audio signal from the operator's microphone is used to obtain the identification codes of those compo
Externí odkaz:
https://doaj.org/article/1960dea3ce7347338836c825d482f571
Autor:
Javier Tejedor, Doroteo T. Toledano
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-20 (2024)
Abstract The vast amount of information stored in audio repositories makes necessary the development of efficient and automatic methods to search on audio content. In that direction, search on speech (SoS) has received much attention in the last deca
Externí odkaz:
https://doaj.org/article/95bcd5341c414988a7d5e784387d37e8
Publikováno v:
Sensors, Vol 24, Iss 22, p 7151 (2024)
(1) Background: As far back as the 1930s, it was already thought that gestures, clothing, speech, posture, and gait could express an individual’s personality. Different research programs, some focused on linguistic cues, were launched, though resul
Externí odkaz:
https://doaj.org/article/f552f013af524c8b89e83643888d7e70
Publikováno v:
PLoS ONE, Vol 19, Iss 7, p e0303994 (2024)
In recent years, the relation between Sound Event Detection (SED) and Source Separation (SSep) has received a growing interest, in particular, with the aim to enhance the performance of SED by leveraging the synergies between both tasks. In this pape
Externí odkaz:
https://doaj.org/article/9f9b6457ad854b71aa48a7d3e21b8756
Publikováno v:
IEEE Access, Vol 9, Pp 89029-89042 (2021)
Sound Event Detection is a task with a rising relevance over the recent years in the field of audio signal processing, due to the creation of specific datasets such as Google AudioSet or DESED (Domestic Environment Sound Event Detection) and the intr
Externí odkaz:
https://doaj.org/article/30b877a58fa3460ab7e9e88353354f98
Autor:
Javier Tejedor, Doroteo T. Toledano, Paula Lopez-Otero, Laura Docio-Fernandez, Ana R. Montalvo, Jose M. Ramirez, Mikel Peñagarikano, Luis Javier Rodriguez-Fuentes
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2019, Iss 1, Pp 1-37 (2019)
Abstract Search on speech (SoS) is a challenging area due to the huge amount of information stored in audio and video repositories. Spoken term detection (STD) is an SoS-related task aiming to retrieve data from a speech repository given a textual re
Externí odkaz:
https://doaj.org/article/e4f54e3cb6b240c8b4c458763bcf4470
Autor:
Javier Tejedor, Doroteo T. Toledano, Paula Lopez-Otero, Laura Docio-Fernandez, Mikel Peñagarikano, Luis Javier Rodriguez-Fuentes, Antonio Moreno-Sandoval
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2019, Iss 1, Pp 1-29 (2019)
Abstract The huge amount of information stored in audio and video repositories makes search on speech (SoS) a priority area nowadays. Within SoS, Query-by-Example Spoken Term Detection (QbE STD) aims to retrieve data from a speech repository given a
Externí odkaz:
https://doaj.org/article/e0882af3a5f046d09d323529b13d1d05
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2019, Iss 1, Pp 1-18 (2019)
Abstract Audio signals represent a wide diversity of acoustic events, from background environmental noise to spoken communication. Machine learning models such as neural networks have already been proposed for audio signal modeling, where recurrent s
Externí odkaz:
https://doaj.org/article/b982cad8e8874ccda8e178833d78cb69
Publikováno v:
Applied Sciences, Vol 12, Iss 3, p 1580 (2022)
Client conversations in contact centers are nowadays routinely recorded for a number of reasons—in many cases, just because it is required by current legislation. However, even if not required, conversations between customers and agents can be a va
Externí odkaz:
https://doaj.org/article/8ff12e6643f84878b5c906efe85c0c39
Autor:
Javier Tejedor, Doroteo T. Toledano, Paula Lopez-Otero, Laura Docio-Fernandez, Jorge Proença, Fernando Perdigão, Fernando García-Granada, Emilio Sanchis, Anna Pompili, Alberto Abad
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2018, Iss 1, Pp 1-25 (2018)
Abstract Query-by-example Spoken Term Detection (QbE STD) aims to retrieve data from a speech repository given an acoustic (spoken) query containing the term of interest as the input. This paper presents the systems submitted to the ALBAYZIN QbE STD
Externí odkaz:
https://doaj.org/article/f60f9bd8673d4ea5b5635c0ea95069d3