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4. Multimodal Speaker Diarization Of Real-World Meetings Using D-Vectors With Spatial Features

Multimodal Speaker Diarization Of Real-World Meetings Using D-Vectors With Spatial Features

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IEEE ICASSP 2020 Virtual Conference May 2020

Deep neural network based audio embeddings (d-vectors) have demonstrated superior performance in audio-only speaker diarization compared to traditional acoustic features such as mel-frequency cepstral coefficients (MFCCs) and i-vectors. However, there has

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Multimodal Speaker Diarization Of Real-World Meetings Using D-Vectors With Spatial Features

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Deep neural network based audio embeddings (d-vectors) have demonstrated superior performance in audio-only speaker diarization compared to traditional acoustic features such as mel-frequency cepstral coefficients (MFCCs) and i-vectors. However, there has