Speaking to Machine
Validity of Pronunciation Assessment by Technology-Driven Systems
Datos Bibliográficos
| ID | 22200671 |
|---|---|
| Autores | Ali Babaeian (Center for Assessment, autor de correspondencia) |
| Año | 2025 |
| Volumen | 5 |
| Número | 3 |
| Páginas | 276-279 |
| Fecha de publicación | 2025-05-30 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Integrated Journal for Research in Arts and Humanities (JOURNAL) |
| Identificadores de la revista | ISSN: 2583-1712 • E-ISSN: 2583-1712 |
| Editorial | Stallion Publication (PUBLISHER) |
| DOI | 10.55544/ijrah.5.3.31 |
| OpenAlex | W4410884879 |
| Idioma | EN |
| Referencias citadas | 12 |
This mini review discusses the validity of technology-driven pronunciation assessment systems, focusing on their alignment with intelligibility as the central criterion of communicative competence. The review highlights the need for theoretical recalibration to ensure valid and inclusive assessment practices in high- and low-stakes contexts by interrogating scoring mechanisms, native-norm dependencies, and human-machine correlations
Linguistics · Natural language processing · Pronunciation · Computer Science · EFL/ESL Teaching and Learning · Philosophy · Phonetics and Phonology Research · Psychology · Speech and dialogue systems · Artificial Intelligence
| Velocidad de citación | historical |
|---|---|
| Altamente citado | No |