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A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings
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| Published in: | EURASIP Journal on Audio, Speech, and Music Processing |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1867301674411884544 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | EURASIP Journal on Audio, Speech, and Music Processing |
| description | |
| discipline_display | Radio and TV |
| discipline_facet | Radio and TV |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:58751 |
| institution | FRELIP |
| journal_source_facet | EURASIP Journal on Audio, Speech, and Music Processing |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings Radio and TV General Radio and TV |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Radio and TV General Radio and TV Radio and TV General Radio and TV |
| subject_facet | Radio and TV General Radio and TV |
| title | A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings |
| title_auth | A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings |
| title_full | A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings |
| title_fullStr | A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings |
| title_full_unstemmed | A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings |
| title_short | A unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings |
| title_sort | a unified deep learning framework for estimating acoustic context parameters from first order ambisonic speech recordings |
| topic | Radio and TV General Radio and TV |
| url | https://link.springer.com/article/10.1186/s13636-025-00443-0 |