Neural-network speech processing for toys and consumer electronics

The ongoing challenge in speech research is the recognition of continuous, unconstrained speech. In comparison, isolated word recognition with small vocabularies is easy. Many research efforts and commercial ventures aim at the high end problem. Sensory Inc. has successfully focused on the low end,...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE expert 1996-08, Vol.11 (4), p.4-5
1. Verfasser: Mozer, M.C.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 5
container_issue 4
container_start_page 4
container_title IEEE expert
container_volume 11
creator Mozer, M.C.
description The ongoing challenge in speech research is the recognition of continuous, unconstrained speech. In comparison, isolated word recognition with small vocabularies is easy. Many research efforts and commercial ventures aim at the high end problem. Sensory Inc. has successfully focused on the low end, producing a family of inexpensive speech recognition ICs for markets such as interactive toys, consumer electronics, electronic learning aids, telecommunication devices, security systems, and household appliances. These markets are extremely cost conscious and demand solutions in the under five dollar price range. Previous low cost solutions relied on coarse properties of the speech signal, such as the amplitude envelope or zero crossing rates, and typically yielded poor recognition performance. Digital signal processor based approaches can achieve adequate performance but are beyond the low cost market's reach. Sensory uses a neural network based approach that provides robust performance at a low cost. Sensory's general purpose RSC-164 controller performs four speech recognition functions.
doi_str_mv 10.1109/64.511766
format Article
fullrecord <record><control><sourceid>crossref_RIE</sourceid><recordid>TN_cdi_ieee_primary_511766</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>511766</ieee_id><sourcerecordid>10_1109_64_511766</sourcerecordid><originalsourceid>FETCH-LOGICAL-c121t-59837f8457be6d59dcd94e47b0f42ab0307ad44f856fd8785ce45b1244bd1f3</originalsourceid><addsrcrecordid>eNo9jz1PwzAURS0EEqEwsDJ5ZUh5Tp4_MkJFAamCAfYosZ8hkMaRnQr13wNKxXSHe3Skw9ilgKUQUN0oXEohtFJHLCtKjXmFoI9ZBsbIvAKAU3aW0ieAQNQqY3fPtItNnw80fYf4xdNIZD_4GIOllLrhnfsQ-RT2iTeD4zYMabelyKknO8UwdDadsxPf9IkuDrtgr-v7t9Vjvnl5eFrdbnIrCjHlsjKl9galbkk5WTnrKiTULXgsmhZK0I1D9EYq74w20hLKVhSIrRO-XLDr2WpjSCmSr8fYbZu4rwXUf-m1wnpO_2WvZrYjon_ucP4Av6NUdg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Neural-network speech processing for toys and consumer electronics</title><source>IEEE Electronic Library (IEL)</source><creator>Mozer, M.C.</creator><creatorcontrib>Mozer, M.C.</creatorcontrib><description>The ongoing challenge in speech research is the recognition of continuous, unconstrained speech. In comparison, isolated word recognition with small vocabularies is easy. Many research efforts and commercial ventures aim at the high end problem. Sensory Inc. has successfully focused on the low end, producing a family of inexpensive speech recognition ICs for markets such as interactive toys, consumer electronics, electronic learning aids, telecommunication devices, security systems, and household appliances. These markets are extremely cost conscious and demand solutions in the under five dollar price range. Previous low cost solutions relied on coarse properties of the speech signal, such as the amplitude envelope or zero crossing rates, and typically yielded poor recognition performance. Digital signal processor based approaches can achieve adequate performance but are beyond the low cost market's reach. Sensory uses a neural network based approach that provides robust performance at a low cost. Sensory's general purpose RSC-164 controller performs four speech recognition functions.</description><identifier>ISSN: 0885-9000</identifier><identifier>EISSN: 2374-9407</identifier><identifier>DOI: 10.1109/64.511766</identifier><identifier>CODEN: IEEXE7</identifier><language>eng</language><publisher>IEEE</publisher><subject>Consumer electronics ; Costs ; Digital signal processors ; Electronic learning ; Home appliances ; Neural networks ; Security ; Speech processing ; Speech recognition ; Vocabulary</subject><ispartof>IEEE expert, 1996-08, Vol.11 (4), p.4-5</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c121t-59837f8457be6d59dcd94e47b0f42ab0307ad44f856fd8785ce45b1244bd1f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/511766$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/511766$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Mozer, M.C.</creatorcontrib><title>Neural-network speech processing for toys and consumer electronics</title><title>IEEE expert</title><addtitle>EX-M</addtitle><description>The ongoing challenge in speech research is the recognition of continuous, unconstrained speech. In comparison, isolated word recognition with small vocabularies is easy. Many research efforts and commercial ventures aim at the high end problem. Sensory Inc. has successfully focused on the low end, producing a family of inexpensive speech recognition ICs for markets such as interactive toys, consumer electronics, electronic learning aids, telecommunication devices, security systems, and household appliances. These markets are extremely cost conscious and demand solutions in the under five dollar price range. Previous low cost solutions relied on coarse properties of the speech signal, such as the amplitude envelope or zero crossing rates, and typically yielded poor recognition performance. Digital signal processor based approaches can achieve adequate performance but are beyond the low cost market's reach. Sensory uses a neural network based approach that provides robust performance at a low cost. Sensory's general purpose RSC-164 controller performs four speech recognition functions.</description><subject>Consumer electronics</subject><subject>Costs</subject><subject>Digital signal processors</subject><subject>Electronic learning</subject><subject>Home appliances</subject><subject>Neural networks</subject><subject>Security</subject><subject>Speech processing</subject><subject>Speech recognition</subject><subject>Vocabulary</subject><issn>0885-9000</issn><issn>2374-9407</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1996</creationdate><recordtype>article</recordtype><recordid>eNo9jz1PwzAURS0EEqEwsDJ5ZUh5Tp4_MkJFAamCAfYosZ8hkMaRnQr13wNKxXSHe3Skw9ilgKUQUN0oXEohtFJHLCtKjXmFoI9ZBsbIvAKAU3aW0ieAQNQqY3fPtItNnw80fYf4xdNIZD_4GIOllLrhnfsQ-RT2iTeD4zYMabelyKknO8UwdDadsxPf9IkuDrtgr-v7t9Vjvnl5eFrdbnIrCjHlsjKl9galbkk5WTnrKiTULXgsmhZK0I1D9EYq74w20hLKVhSIrRO-XLDr2WpjSCmSr8fYbZu4rwXUf-m1wnpO_2WvZrYjon_ucP4Av6NUdg</recordid><startdate>199608</startdate><enddate>199608</enddate><creator>Mozer, M.C.</creator><general>IEEE</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>199608</creationdate><title>Neural-network speech processing for toys and consumer electronics</title><author>Mozer, M.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c121t-59837f8457be6d59dcd94e47b0f42ab0307ad44f856fd8785ce45b1244bd1f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Consumer electronics</topic><topic>Costs</topic><topic>Digital signal processors</topic><topic>Electronic learning</topic><topic>Home appliances</topic><topic>Neural networks</topic><topic>Security</topic><topic>Speech processing</topic><topic>Speech recognition</topic><topic>Vocabulary</topic><toplevel>online_resources</toplevel><creatorcontrib>Mozer, M.C.</creatorcontrib><collection>CrossRef</collection><jtitle>IEEE expert</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Mozer, M.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neural-network speech processing for toys and consumer electronics</atitle><jtitle>IEEE expert</jtitle><stitle>EX-M</stitle><date>1996-08</date><risdate>1996</risdate><volume>11</volume><issue>4</issue><spage>4</spage><epage>5</epage><pages>4-5</pages><issn>0885-9000</issn><eissn>2374-9407</eissn><coden>IEEXE7</coden><abstract>The ongoing challenge in speech research is the recognition of continuous, unconstrained speech. In comparison, isolated word recognition with small vocabularies is easy. Many research efforts and commercial ventures aim at the high end problem. Sensory Inc. has successfully focused on the low end, producing a family of inexpensive speech recognition ICs for markets such as interactive toys, consumer electronics, electronic learning aids, telecommunication devices, security systems, and household appliances. These markets are extremely cost conscious and demand solutions in the under five dollar price range. Previous low cost solutions relied on coarse properties of the speech signal, such as the amplitude envelope or zero crossing rates, and typically yielded poor recognition performance. Digital signal processor based approaches can achieve adequate performance but are beyond the low cost market's reach. Sensory uses a neural network based approach that provides robust performance at a low cost. Sensory's general purpose RSC-164 controller performs four speech recognition functions.</abstract><pub>IEEE</pub><doi>10.1109/64.511766</doi><tpages>2</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0885-9000
ispartof IEEE expert, 1996-08, Vol.11 (4), p.4-5
issn 0885-9000
2374-9407
language eng
recordid cdi_ieee_primary_511766
source IEEE Electronic Library (IEL)
subjects Consumer electronics
Costs
Digital signal processors
Electronic learning
Home appliances
Neural networks
Security
Speech processing
Speech recognition
Vocabulary
title Neural-network speech processing for toys and consumer electronics
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T13%3A38%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Neural-network%20speech%20processing%20for%20toys%20and%20consumer%20electronics&rft.jtitle=IEEE%20expert&rft.au=Mozer,%20M.C.&rft.date=1996-08&rft.volume=11&rft.issue=4&rft.spage=4&rft.epage=5&rft.pages=4-5&rft.issn=0885-9000&rft.eissn=2374-9407&rft.coden=IEEXE7&rft_id=info:doi/10.1109/64.511766&rft_dat=%3Ccrossref_RIE%3E10_1109_64_511766%3C/crossref_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=511766&rfr_iscdi=true