Age Differences in Identifying Words in Synthetic Speech

Roring, Roy W.; Hines, Franklin G.; Charness, Neil

doi:10.1518/001872007779598055

Cited by 26 publications

(28 citation statements)

References 23 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The speed of fast is approximately 20% faster than normal. This 20% difference resembles studies in the literature (Woodall & Burgoon 1983), but it is smaller than the parameters in other works (in Roring et al 2007, fast was 40% faster than normal; in Goodman et al 1999, twice/half speed to normal speed was used). Moderately slow was added between normal and slow because in a preliminary experiment participants preferred such an intermediate speed.…”

Section: B Conditionssupporting

confidence: 66%

“…When people first hear a synthesized voice they experience some comprehension difficulty, but comprehension improves after they get accustomed to listening to the synthesized voice, especially after the first five sentences (Venkatagiri 1994). In a study of the effect of slow speed in a synthesized voice, contrary to the authors' initial expectations, fast speech (210 WPM: originally labeled "normal" but we changed the designation for consistency with other studies) outperformed normal speech (150 WPM) by approximately 5% for word identification (Roring, Hines & Charness 2007). Their study also showed that natural speech was comprehended better than synthesized speech, and a younger population comprehended better than an older population.…”

Section: B Related Research In Spoken Dialogsmentioning

confidence: 77%

“…-A robot that provides normal speech will be perceived as more credible than a robot that provides normal and slow speech (as Simonds et al 2006 reported for human communication). -Normal and fast speech will provide better comprehension than slow speech (as Pisoni et al 1985 andSimonds et al 2006 reported for human communication and Roring et al 2007 reported for synthesized voices). -Overall, normal and fast speech will be perceived as a better speech rate than a slow speech rate.…”

Section: Hypothesis 1a: Robots Should Not Speak More Slowly Than Normalmentioning

confidence: 92%

See 2 more Smart Citations

What is the appropriate speech rate for a communication robot?

Shimada¹,

Kanda²

2012

inter stud

View full text Add to dashboard Cite

This study investigates the influence of a robot's speech rate. In human communication, slow speech is considered boring, speech at normal speed is perceived as credible, and fast speech is perceived as competent. To seek the appropriate speech rate for robots, we test whether these tendencies are replicated in human-robot interaction by conducting an experiment with four rates of speech: fast, normal, moderately slow, and slow. Our experimental results reveal a rather surprising trend. Participants prefer normal and moderately slow speech to fast speech. A robot that provides normal or moderately slow speech is perceived as competent. We further study how context affects this perception. In a situation where the robot and participants talk while walking, we found that slow speech was the most comprehensible. In addition, slow speech is subjectively perceived as good as moderately slow and normal speech.

show abstract

Section: B Conditionssupporting

confidence: 66%

Section: B Related Research In Spoken Dialogsmentioning

confidence: 77%

Section: Hypothesis 1a: Robots Should Not Speak More Slowly Than Normalmentioning

confidence: 92%

See 1 more Smart Citation

What is the appropriate speech rate for a communication robot?

Shimada¹,

Kanda²

2012

inter stud

View full text Add to dashboard Cite

show abstract

“…There is a growing body of work on intelligibility of the output component of SDS, speech synthesis, to older people (Smither 1993;Black et al 2002;Humes and Floyd 2005;Langner and Black 2005;Lines and Hone 2006;Hardee 2007;Roring et al 2007). Unfortunately, most of this research examines speech synthesis technologies that are no longer state-of-the-art, such as formant synthesis and diphone synthesis.…”

Section: Introductionmentioning

confidence: 99%

The MATCH corpus: a corpus of older and younger users’ interactions with spoken dialogue systems

Georgila

Wolters

Moore

et al. 2010

Lang Resources & Evaluation

View full text Add to dashboard Cite

We present the MATCH corpus, a unique data set of 447 dialogues in which 26 older and 24 younger adults interact with nine different spoken dialogue systems. The systems varied in the number of options presented and the confirmation strategy used. The corpus also contains information about the users' cognitive abilities and detailed usability assessments of each dialogue system. The corpus, which was collected using a Wizard-of-Oz methodology, has been fully transcribed and annotated with dialogue acts and ''Information State Update'' (ISU) representations of dialogue context. Dialogue act and ISU annotations were This research was supported by the MATCH project (SHEFC-HR04016, performed semi-automatically. In addition to describing the corpus collection and annotation, we present a quantitative analysis of the interaction behaviour of older and younger users and discuss further applications of the corpus. We expect that the corpus will provide a key resource for modelling older people's interaction with spoken dialogue systems.

show abstract

“…13 Older people find synthetic speech more difficult to understand than younger people. 14,15 However, most related work [14][15][16][17][18][19] has focused on older speech synthesis technology and may therefore overestimate intelligibility problems. Here, we used publicly available implementations of the two main current speech synthesis approaches, statistical parametric synthesis 20,21 and unit selection 22,23 (figure 1).…”

mentioning

confidence: 99%

Can older people remember medication reminders presented using synthetic speech?

Wolters

Johnson

Campbell

et al. 2014

Journal of the American Medical Informatics Association

View full text Add to dashboard Cite

Reminders are often part of interventions to help older people adhere to complicated medication regimes. Computer-generated (synthetic) speech is ideal for tailoring reminders to different medication regimes. Since synthetic speech may be less intelligible than human speech, in particular under difficult listening conditions, we assessed how well older people can recall synthetic speech reminders for medications. 44 participants aged 50–80 with no cognitive impairment recalled reminders for one or four medications after a short distraction. We varied background noise, speech quality, and message design. Reminders were presented using a human voice and two synthetic voices. Data were analyzed using generalized linear mixed models. Reminder recall was satisfactory if reminders were restricted to one familiar medication, regardless of the voice used. Repeating medication names supported recall of lists of medications. We conclude that spoken reminders should build on familiar information and be integrated with other adherence support measures.

show abstract

Age Differences in Identifying Words in Synthetic Speech

Abstract: Systems using synthetic speech should avoid presenting words in isolation, and rich contextual support should be consistently adopted. Synthetic speech fidelity must be improved significantly before becoming truly useful for older adult populations.

Cited by 26 publications

References 23 publications

What is the appropriate speech rate for a communication robot?

What is the appropriate speech rate for a communication robot?

The MATCH corpus: a corpus of older and younger users’ interactions with spoken dialogue systems

Can older people remember medication reminders presented using synthetic speech?

Contact Info

Product

Resources

About