| DC Field | Value | Language |
|---|
| dc.contributor.author | Zhengyu Chen | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2026-07-31T08:16:53Z | - |
| dc.date.available | 2026-07-31T08:16:53Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.citation | Zhengyu Chen. Software for recognizing speaker by voice / Zhengyu Chen // Информационные технологии и управление : материалы 62-ой научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 13–17 апреля 2026 года / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: А. А. Навроцкий [и др.]. – Минск, 2026. – С. 131. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/65125 | - |
| dc.description.abstract | This system, based on the lightweight Flask web framework and the ECAPA-TDNN deep learning model, designs and implements
a complete speaker recognition system.[1] The backend uses Flask to build a RESTful API service, with core functionalities
covering four main modules: voiceprint registration, voiceprint recognition, user management, and audio comparison. The
database layer uses SQLite to store user information and embedding vectors, and the frontend uses the Jinja2 template engine to
dynamically render pages, displaying recognition results intuitively as a progress bar. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | speaker recognition | en_US |
| dc.subject | deep learning model | en_US |
| dc.subject | embedding vectors | en_US |
| dc.title | Software for recognizing speaker by voice | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Информационные технологии и управление : материалы 62-й научной конференции аспирантов, магистрантов и студентов БГУИР (2026)
|
