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,...
Gespeichert in:
Veröffentlicht in: | IEEE expert 1996-08, Vol.11 (4), p.4-5 |
---|---|
1. Verfasser: | |
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 |