all AI news
The NeurIPS 2023 Machine Learning for Audio Workshop: Affective Audio Benchmarks and Novel Data
March 22, 2024, 4:48 a.m. | Alice Baird, Rachel Manzelli, Panagiotis Tzirakis, Chris Gagne, Haoqi Li, Sadie Allen, Sander Dieleman, Brian Kulis, Shrikanth S. Narayanan, Alan Cowe
cs.CL updates on arXiv.org arxiv.org
Abstract: The NeurIPS 2023 Machine Learning for Audio Workshop brings together machine learning (ML) experts from various audio domains. There are several valuable audio-driven ML tasks, from speech emotion recognition to audio event detection, but the community is sparse compared to other ML areas, e.g., computer vision or natural language processing. A major limitation with audio is the available data; with audio being a time-dependent modality, high-quality data collection is time-consuming and costly, making it challenging …
abstract arxiv audio benchmarks community cs.cl cs.sd data detection domains eess.as emotion event experts machine machine learning neurips novel recognition speech speech emotion tasks together type workshop
More from arxiv.org / cs.CL updates on arXiv.org
Benchmarking LLMs via Uncertainty Quantification
2 days, 2 hours ago |
arxiv.org
CARE: Extracting Experimental Findings From Clinical Literature
2 days, 2 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Principal Data Engineering Manager
@ Microsoft | Redmond, Washington, United States
Machine Learning Engineer
@ Apple | San Diego, California, United States