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Competitive Evaluation of Commercially Available Speech Recognizers in Multiple Languages

Sloane, Zachary; Burger, Susanne; Yang, Jie

Abstract:

Recent improvements in speech recognition technology have resulted in products that can now demonstrate commercial value in a variety of applications. Many vendors are marketing products which combine ASR applications including continuous dictation, command-and-control interfaces, and transcription of recorded speech at an accuracy of 98%. In this study, we measured the accuracy of certain commercially available desktop speech recognition engines in multiple languages. Using word error rate as a benchmark, this work compares recognition accuracy across eight languages and the products of three manufacturers. Results show that two systems performed almost the same while a third system recognized at lower accuracy, although none of the systems reached the claimed accuracy. Read speech was recognized better than spontaneous speech. The systems for US-English, Japanese and Spanish showed higher accuracy than the systems for UK-English, German, French and Chinese.


Verlagsausgabe §
DOI: 10.5445/IR/1000166410
Veröffentlicht am 27.02.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2006
Sprache Englisch
Identifikator KITopen-ID: 1000166410
Erschienen in Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06). Ed.: N. Calzolari, K. Choukri, A. Gangemi, B. Maegaard, J. Mariani, J. Odijk, D. Tapias
Veranstaltung 5th Language Resources and Evaluation Conference (LREC 2006), Genua, Italien, 22.05.2006 – 28.05.2006
Verlag Association for Computational Linguistics (ACL)
Seiten 809-814
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