Name
Abstract | ||
|---|---|---|
During face-to-face conversations, adults with autism frequently use atypical rhythms and sounds in their speech (prosody), which can result in misunderstandings and miscommunication. SayWAT is a Wearable Assistive Technology that provides feedback to wearers about their prosody during face-to-face conversations. In this paper, we describe the design process that led to five design guidelines that governed the development of SayWAT and present results from two studies involving our prototype solution. Our results indicate that wearable assistive technologies can automatically detect atypical prosody and deliver feedback in real time without disrupting the wearer or the conversation partner. Additionally, we provide suggestions for wearable assistive technologies for social support. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2858036.2858215 | CHI |
Keywords | Field | DocType |
Autism, communication, prosody, wearable computing, social skills, assistive technology | Autism,Prosody,Conversation,Computer science,Wearable computer,Face-to-face,Social skills,Human–computer interaction,Social support | Conference |
Citations | PageRank | References |
14 | 0.61 | 11 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| LouAnne Boyd | 1 | 94 | 6.77 |
| Alejandro Rangel | 2 | 57 | 2.91 |
| Helen Tomimbang | 3 | 14 | 0.61 |
| Andrea Conejo-Toledo | 4 | 14 | 0.61 |
| Kanika Patel | 5 | 14 | 0.95 |
| Monica Tentori | 6 | 688 | 57.82 |
| Gillian Hayes | 7 | 1852 | 155.64 |