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Natural Voice Recognition

Natural Voice Recognition. Thomas Krippgans. Email: Thomas.Krippgans@Temic.de Tel.: + 49 731 3994 106 FAX: +49 731 3994 251. R & D. T EMIC. 5.300 Employee $ 800 Mio. turn over. Speech Processing. Automotive. Telecommunication. Embedded.

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Natural Voice Recognition

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  1. Natural Voice Recognition Thomas Krippgans Email: Thomas.Krippgans@Temic.de Tel.: + 49 731 3994 106 FAX: +49 731 3994 251

  2. R & D TEMIC 5.300 Employee $ 800 Mio. turn over Speech Processing Automotive Telecommunication Embedded Krippgans

  3. Locations, Employees, Capabilities in Speech Processing Bangalore: 4 employees autm. Transcritption Auburn Hills: 1 employee Sales 10 Key Account Ulm-DC RC: 35 employees Acoustics Recognition (NLU) Synthesis Verification Text Interpretation Palo Alto: 40 employees Telematics Communication systems Speech Recognition Mobile Internet Ulm-TEMIC: 75 employees Acoustics Voice Recognition Dialog Design Integration Krippgans

  4. Deutsche Bahn DB Embedded Systems Telecommunication Automotive In 1999 about 12.000 Ports In 1999 about 75.000 Units Launching Customer Thomson multimedia Belinguasoft-CAD Systems THB Bury Tobit Toshiba Krippgans

  5. At the beginning is: “Dada”

  6. Dada iiiiiii Natural Voice Krippgans

  7. Natural Voice 8-) 8-) Papa 8-) Krippgans

  8. Natural Voice • In age of 7 to 10 month kids start to move their lower jaw • every of them, in over more than 27 different languages, use • “Dada” “Mama” “Gogo” as the common words • this kids use the so called Protowords will be find in all languages Krippgans

  9. Natural Voice To be or not to be that’s the question !? ! ! ? ? ?? Krippgans

  10. Natural Voice Recognition For applications in the world of Service Provider using Natural Language Recognition on thing is importand: • Transaction Success Rate (TSR) Krippgans

  11. What is Natural Language Understanding? Some definitions: The user can say anything she/he wants... • ... and the system picks key words (word spotting).“I would like to record a message” • ... and the system picks key phrases (phrase spotting).“Tomorrow I would like to go from Ulmto Munich” “Do I have anew message?” vs. “I would like to record anew message” • ... and the system recognizes all words and attempts to understand them. (Word Hypothesis Graph and Parser from Temic ) Krippgans

  12. recognition result speech signal parsing result Natural Language Understanding Krippgans

  13. Results from a Field Trial • Support Hotline System; Experience from the ACCeSS Project (EU founded) • A incoming call routing system • Natural Language Recognition 2nd Generation (Parsing and NLU Dialogmanager) • Evaluation of 1.500 Dialogues during a three months field trial • Installed in a Call Center enviroment Krippgans

  14. Results from a Field Trial • We evaluated 1,528 dialogues with 9,159 recorded utterances, 12,886 total words • Dialogue Duration 70 sec • Hang-Ups 13 % • Average Success Rate 97 % Krippgans

  15. Spoken Language Dialogue Main components of spoken language dialogue systems recognition understanding dialogue planning next dialogue step information, meaning acoustic data ASCII Krippgans

  16. Call Center Integration A C D Speech Recognizer Dialogue Manager Line Interface System Control Speech Synthesis Database Interface Database server LAN User Operator Krippgans

  17. How many Users are Out There? Krippgans

  18. == 16 ASR Ports 30 Server == 240 ASR Ports 2.400 ASR Ports == Solutions for huge subscriber basesStarRec KXL (PCI/cPCI) Krippgans

  19. Speech Recognition Solution (High Integrated NLU) - 19 inch slide- in module - up to 240 ports NLU; good for 600 telephone ports - comfortable maintenance - a way to design huge systems Krippgans

  20. Tool‘s GDS (Grammar Design Software) Krippgans

  21. ? Dada iiiiiii No Transaction Success Rate Krippgans

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