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Title:PRIPRAVA OKOLJA ZA VREDNOTENJE ZMOGLJIVOSTI RAZPOZNAVALNIKA GOVORA ZA STORITVE IVR
Authors:ID Šerc, Matic (Author)
ID Žgank, Andrej (Mentor) More about this mentor... New window
ID Imperl, Bojan (Comentor)
Files:.pdf UNI_Serc_Matic_2010.pdf (1,03 MB)
MD5: 99EFF215174E056155833612D7123124
PID: 20.500.12556/dkum/beb24b22-3d35-406a-88c8-b56cd60e04f6
 
Language:Slovenian
Work type:Bachelor thesis/paper
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu smo pripravili okolje za vrednotenje zmogljivosti razpoznavalnika govora IskratelASR za storitve IVR in ovrednotili okvirna območja, znotraj katerih je na posamezni strojni konfiguraciji smiselno izvajati meritve. Območja smo za 8 reprezentativnih scenarijev vrednotili z vidika števila kanalov, ki jih je sistem zmožen procesirati sočasno. Pri tem smo spremljali rezultate procesiranja in obremenitev strežnika. Z uporabo pripravljenega okolja in ugotovitev v nalogi bo mogoče izvesti natančne meritve, katerih rezultati bodo služili za pripravo matematičnega modela za izračun maksimalnega števila sočasnih kanalov glede na lastnosti in način uporabe sistema ASR.
Keywords:storitve interaktivnega govornega odziva, vrednotenje zmogljivosti, avtomatsko razpoznavanje govora, komunikacija človek-stroj
Place of publishing:Maribor
Publisher:[M. Šerc]
Year of publishing:2010
PID:20.500.12556/DKUM-16057 New window
UDC:004.93(043.2)
COBISS.SI-ID:14672150 New window
NUK URN:URN:SI:UM:DK:6GTPR7F2
Publication date in DKUM:13.12.2010
Views:2309
Downloads:136
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:AUTOMATIC SPEECH RECOGNITION PERFORMANCE EVALUATION FRAMEWORK FOR IVR SERVICES
Abstract:In the diploma thesis, we prepared a framework for ASR performance evaluation, which can be used with IskratelASR software. We also evaluated limits for further performance measurements on multiple hardware configurations. The performance was evaluated in terms of number of simultaneous channels which can be handled by the system for 8 representative scenarios. During the measurements, we monitored server load and results. By using prepared environment and findings from this work, further measurements and finally a preparation of a mathematical model for performance evaluation based on ASR properties can be accomplished.
Keywords:interactive voice response services, performance evaluation, automatic speech recognition, human-computer interaction


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