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PrepTalk

PrepTalk. a Prep rocessor for Talk ing book production. Ted van der Togt, Dedicon, Amsterdam. Situation. Growing demand for audio products with growing and more diverse user group Quality of ‘standard’ TTS ‘not good enough Limited budget, more narrators no option

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PrepTalk

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  1. PrepTalk a Preprocessor for Talking book production Ted van der Togt, Dedicon, Amsterdam

  2. Situation • Growing demand for audio products with growing and more diverse user group • Quality of ‘standard’ TTS ‘not good enough • Limited budget, more narrators no option • Need for speed (newspapers, higher education)

  3. Objectives • Build (components for) TTS production • Integrate with Daisy Pipeline • Focus on: • Quality improvement • Workflow efficiency • Resource optimization

  4. Project partners and funding • Dutchear (speech synthesis) • Polderland & van den Heuvel HLT (language & speech technology) • Co-financed by: • VOB (Dutch public library organization) • several funds

  5. A) TTS Quality improvement • TTS voices are not perfect • Documents containing ‘foreign’ text, names • Ambiguity inherent to language • TTS software sometimes ‘too smart’

  6. B) Workflow efficiency • Collaborative web portal based approach, showing status, priority, etc. • Central lexicon accumulates knowledge about exceptions • Prioritization of issues within one document when time is limited

  7. C) Resource optimization • Time needed for quality check • Time needed to fix incorrect pronunciation • Licenses on TTS software • Licenses on lexica • Licenses on other tools

  8. PrepTalk process • Workflow with 3 steps: • Automatic document analysis (Daisy XML) • Human (interactive) evaluation and correction • Daisy Pipeline Narrator adapted for processing pronunciation information (in SSML)

  9. 1. Analysis • Sentence detection (+named entity recognition) • Check against lexicon (corpus spoken Dutch) • Pattern recognition (numbers etc.) • Suggestions (ambiguity, spelling mistake)

  10. 2. Editing environment • Evaluate issues based on ‘importance’. • Improve pronunciation with either alternative text or phonemes. • Listen to corrected text within context. • Add solutions to central lexicon.

  11. 3. Daisy Pipeline Narrator adapted • SSML to describe pronunciation information. • X-SAMPA as phonetic alphabet. • TTS engine independent. • Connection to TTS server using SOAP

  12. Demo Example: IFLA Newsletter ...

  13. Demonstration

  14. System Architecture

  15. Postbus 24 5360 AA Grave The Netherlands T+ 31 (0) 486 486 486 F+ 31 (0) 486 476 535 Thank you for your attention. For questions:tvdtogt@dedicon.nl

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