Dataset Groups Activity Stream Attention-based beamformers for multi-channel speech recognition The proposed 2D Conv-Attention model is compared with a traditional neural beamformer and multi-head attention based model. BibTex: @dataset{Bhargav_Pulugundla_and_Yang_Gao_and_Brian_King_and_Gokce_Keskin_and_Harish_Mallidi_and_Minhua_Wu_and_Jasha_Droppo_and_Roland_Maas_2024, abstract = {The proposed 2D Conv-Attention model is compared with a traditional neural beamformer and multi-head attention based model.}, author = {Bhargav Pulugundla and Yang Gao and Brian King and Gokce Keskin and Harish Mallidi and Minhua Wu and Jasha Droppo and Roland Maas}, doi = {10.57702/9bq5bf7a}, institution = {No Organization}, keyword = {'Attention-based beamformers', 'Multi-channel', 'Speech recognition'}, month = {dec}, publisher = {TIB}, title = {Attention-based beamformers for multi-channel speech recognition}, url = {https://service.tib.eu/ldmservice/dataset/attention-based-beamformers-for-multi-channel-speech-recognition}, year = {2024} }
