Text-to-Speech Application in Audio CASI

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Text-to-Speech Application in Audio CASI Evaluation of Implementation and Deployment Jeremy Kraft and Wes Taylor International Field Directors & Technologies Conference 2006 May 21 May 24 www.uwsc.wisc.edu

Outline Text to Speech in ACASI Aspects of Traditional Approach to ACASI Using live voice talent to record items Pros and Cons Aspects of Text to Speech Approach (TTS) Using voices generated artificially via software Examples of Text to Speech Recordings Different Suites Different Styles

UWSC ACASI in CAPI settings Audio Computer-Assisted Self-Interviewing (ACASI) Offers privacy to respondents Increases reporting of socially undesirable behaviors Benefits populations with low literacy rates Respondent see both text and hears audio files played through headphones

ACASI Section Development Process Development of script Hire of voice talent and recording studio Use interviewers or students on campus Record Access to professional studio Edit individual sound files

Traditional UWSC Approach to ACASI Pros of using natural voice Human voice talent is coachable Pronunciation can be fine-tuned Human voice may build more rapport Cons of using natural voice Unconscious inflection in wording Time-consuming Last minute changes are impractical

New Approach to ACASI Recording? Text To Speech (TTS) Bypass voice talent, recording, and editing steps Pros of TTS Greater flexibility for edits late in development Less development time Impersonal approach to sensitive questions Cons of TTS Occasional unclear pronunciation May seem too impersonal Hard to duplicate accents (if desired)

New Approach to ACASI Recording? Previous Research Couper, Mick P., Eleanor Singer, R. Tourangeau. "Does Voice Matter? An Interactive Voice Response (IVR) Experiment." Journal of Official Statistics, 20 (3): 551-570. 2004. Telephone setting No difference found between a recorded human voice, a human-like TTS, and a machine-like TTS Gender had no affect on responses to sensitive items Confirms significant differences between responses elicited by live interviewers (CATI) and those elicited by an automated system (IVR) Other research suggests respondents prefer improved, female voice

Text To Speech (TTS) Software AT&T Natural Voices (www.research.att.com/~ttsweb/tts) US & UK English, Spanish, German, French $295 per voice (base system comes with male & female English voice) Loquendo (www.loquendo.com) Italian, Dutch, US & UK English, Spanish (4 dialects) German, French, Greek, Portuguese, Swedish & Chinese? $750 for 30 audio pay-as-you-go minutes, also available for purchase Festival (www.cstr.ed.ac.uk/projects/festival) Open Source developed by University of Edinburgh US & UK English, Welsh, Spanish

Text To Speech (TTS) Examples What does TTS sound like? How many times did you deliberately damage property that didn't belong to you during the past 12 months? Female Male AT&T: Loquendo: Festival: Human:

Text To Speech (TTS) AT&T Examples (cont d) How many times did you deliberately damage property that didn't belong to you during the past 12 months? Crystal Lauren Claire Mike Rich Rosa Arnaud (tempo) (emphasis) (human) ( Qué es la tasa de cambio?) (Voulez-vous cesser de me cracher dessus pendant que vous parlez!)

Future Plans More research In-house experiment with face to face setting with TTS software and recorded human voice Wait? TTS software will only improve Contact Information Jeremy Kraft Wes Taylor jkraft@ssc.wisc.edu wtaylor@ssc.wisc.edu 608.262.5261 608.263.3349