Chiara Semenzin
Biographic Data
| ID | 8759268 |
|---|---|
| NAME | Chiara Semenzin |
| GIVEN NAMES | Chiara |
| FAMILY NAME | Semenzin |
| SIGNATURE | SEMENZIN C |
| AFFILIATIONS | Laboratoire de Sciences Cognitives et Psycholinguistique |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Towards Large-Scale Data Annotation of Audio from Wearables
Recent developments allow the collection of audio data from lightweight wearable devices, potentially enabling us to study language use from everyday life samples. However, extracting useful information from these data is currently impossible with automatized routines, and overly expensive with trained human annotators. We explore a strategy fit to the 21st century, relying on the collaboration of citizen scientists. A large dataset of infant spe…
Describing vocalizations in young children
Purpose:** Recording young children's vocalizations through wearables is a promising method to assess language development. However, accurately and rapidly annotating these files remains challenging. Online crowdsourcing with the collaboration of citizen scientists could be a feasible solution. In this paper, we assess the extent to which citizen scientists' annotations align with those gathered in the lab for recordings collected from young chil…
No prominent works on this page.
Towards Large-Scale Data Annotation of Audio from Wearables
Recent developments allow the collection of audio data from lightweight wearable devices, potentially enabling us to study language use from everyday life samples. However, extracting useful information from these data is currently impossible with automatized routines, and overly expensive with trained human annotators. We explore a strategy fit to the 21st century, relying on the collaboration of citizen scientists. A large dataset of infant spe…
Describing vocalizations in young children
Purpose:** Recording young children's vocalizations through wearables is a promising method to assess language development. However, accurately and rapidly annotating these files remains challenging. Online crowdsourcing with the collaboration of citizen scientists could be a feasible solution. In this paper, we assess the extent to which citizen scientists' annotations align with those gathered in the lab for recordings collected from young chil…
Annotation (2 works) · Artificial Intelligence (2 works) · Citizen science (2 works) · Computer Science (2 works) · Natural language processing (2 works) · World Wide Web (2 works) · Child Development and Digital Technology (1 work) · Cognitive psychology (1 work) · Crowdsourcing (1 work) · Data collection (1 work)