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- W4381797894 abstract "Speech Emotion Recognition (SER) typically relies on utterance-level solutions. However, emotions conveyed through speech should be considered as discrete speech events with definite temporal boundaries, rather than attributes of the entire utterance. To reflect the fine-grained nature of speech emotions, we propose a new task: Speech Emotion Diarization (SED). Just as Speaker Diarization answers the question of Who speaks when?, Speech Emotion Diarization answers the question of Which emotion appears when?. To facilitate the evaluation of the performance and establish a common benchmark for researchers, we introduce the Zaion Emotion Dataset (ZED), an openly accessible speech emotion dataset that includes non-acted emotions recorded in real-life conditions, along with manually-annotated boundaries of emotion segments within the utterance. We provide competitive baselines and open-source the code and the pre-trained models." @default.
- W4381797894 created "2023-06-24" @default.
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- W4381797894 date "2023-06-22" @default.
- W4381797894 modified "2023-09-27" @default.
- W4381797894 title "Speech Emotion Diarization: Which Emotion Appears When?" @default.
- W4381797894 doi "https://doi.org/10.48550/arxiv.2306.12991" @default.
- W4381797894 hasPublicationYear "2023" @default.
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