A spiking neural network for real-time Spanish vowel phonemes recognition

This paper explores neuromorphic approach capabilities applied to real-time speech processing. A spiking recognition neural network composed of three types of neurons is proposed. These neurons are based on an integrative and fire model and are capable of recognizing auditory frequency patterns, suc...

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Detalles Bibliográficos
Autores: Miró Amarante, María Lourdes, Gómez Rodríguez, Francisco de Asís, Jiménez Fernández, Ángel Francisco, Jiménez Moreno, Gabriel
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2017
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/87921
Acceso en línea:https://hdl.handle.net/11441/87921
https://doi.org/10.1016/j.neucom.2016.12.005
Access Level:acceso abierto
Palabra clave:Neuromorphic engineering
Address event representation (AER)
Event-based processing
FPGA
Digital cochlea
Speech recognition
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oai_identifier_str oai:idus.us.es:11441/87921
network_acronym_str ES
network_name_str España
repository_id_str
spelling A spiking neural network for real-time Spanish vowel phonemes recognitionMiró Amarante, María LourdesGómez Rodríguez, Francisco de AsísJiménez Fernández, Ángel FranciscoJiménez Moreno, GabrielNeuromorphic engineeringAddress event representation (AER)Event-based processingFPGADigital cochleaSpeech recognitionThis paper explores neuromorphic approach capabilities applied to real-time speech processing. A spiking recognition neural network composed of three types of neurons is proposed. These neurons are based on an integrative and fire model and are capable of recognizing auditory frequency patterns, such as vowel phonemes; words are recognized as sequences of vowel phonemes. For demonstrating real-time operation, a complete spiking recognition neural network has been described in VHDL for detecting certain Spanish words, and it has been tested in a FPGA platform. This is a stand-alone and fully hardware system that allows to embed it in a mobile system. To stimulate the network, a spiking digital-filter-based cochlea has been implemented in VHDL. In the implementation, an Address Event Representation (AER) is used for transmitting information between neurons.Ministerio de Economía y Competitividad TEC2012-37868-C04-02/01ElsevierArquitectura y Tecnología de ComputadoresTEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitación2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/87921https://doi.org/10.1016/j.neucom.2016.12.005reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésNeurocomputing, 226 (february 2107), 249-261.TEC2012-37868-C04-02/01https://www.sciencedirect.com/science/article/pii/S0925231216314771info:eu-repo/semantics/openAccessoai:idus.us.es:11441/879212026-06-17T12:51:07Z
dc.title.none.fl_str_mv A spiking neural network for real-time Spanish vowel phonemes recognition
title A spiking neural network for real-time Spanish vowel phonemes recognition
spellingShingle A spiking neural network for real-time Spanish vowel phonemes recognition
Miró Amarante, María Lourdes
Neuromorphic engineering
Address event representation (AER)
Event-based processing
FPGA
Digital cochlea
Speech recognition
title_short A spiking neural network for real-time Spanish vowel phonemes recognition
title_full A spiking neural network for real-time Spanish vowel phonemes recognition
title_fullStr A spiking neural network for real-time Spanish vowel phonemes recognition
title_full_unstemmed A spiking neural network for real-time Spanish vowel phonemes recognition
title_sort A spiking neural network for real-time Spanish vowel phonemes recognition
dc.creator.none.fl_str_mv Miró Amarante, María Lourdes
Gómez Rodríguez, Francisco de Asís
Jiménez Fernández, Ángel Francisco
Jiménez Moreno, Gabriel
author Miró Amarante, María Lourdes
author_facet Miró Amarante, María Lourdes
Gómez Rodríguez, Francisco de Asís
Jiménez Fernández, Ángel Francisco
Jiménez Moreno, Gabriel
author_role author
author2 Gómez Rodríguez, Francisco de Asís
Jiménez Fernández, Ángel Francisco
Jiménez Moreno, Gabriel
author2_role author
author
author
dc.contributor.none.fl_str_mv Arquitectura y Tecnología de Computadores
TEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitación
dc.subject.none.fl_str_mv Neuromorphic engineering
Address event representation (AER)
Event-based processing
FPGA
Digital cochlea
Speech recognition
topic Neuromorphic engineering
Address event representation (AER)
Event-based processing
FPGA
Digital cochlea
Speech recognition
description This paper explores neuromorphic approach capabilities applied to real-time speech processing. A spiking recognition neural network composed of three types of neurons is proposed. These neurons are based on an integrative and fire model and are capable of recognizing auditory frequency patterns, such as vowel phonemes; words are recognized as sequences of vowel phonemes. For demonstrating real-time operation, a complete spiking recognition neural network has been described in VHDL for detecting certain Spanish words, and it has been tested in a FPGA platform. This is a stand-alone and fully hardware system that allows to embed it in a mobile system. To stimulate the network, a spiking digital-filter-based cochlea has been implemented in VHDL. In the implementation, an Address Event Representation (AER) is used for transmitting information between neurons.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/87921
https://doi.org/10.1016/j.neucom.2016.12.005
url https://hdl.handle.net/11441/87921
https://doi.org/10.1016/j.neucom.2016.12.005
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Neurocomputing, 226 (february 2107), 249-261.
TEC2012-37868-C04-02/01
https://www.sciencedirect.com/science/article/pii/S0925231216314771
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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