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

This video program is a part of the Premium package:

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


  • IEEE MemberUS $11.00
  • Society MemberUS $0.00
  • IEEE Student MemberUS $11.00
  • Non-IEEE MemberUS $15.00
Purchase

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

0 views
  • Share
Create Account or Sign In to post comments
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
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