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cs.SD2024
Learning Spatially-Aware Language and Audio Embeddings
Bhavika Devnani, Skyler Seto, Zakaria Aldeneh +5
Humans can picture a sound scene given an imprecise natural language description. For example, it is easy to imagine an acoustic environment given a phrase like "the lion roar came…
cs.SD2024
Can you Remove the Downstream Model for Speaker Recognition with Self-Supervised Speech Features?
Zakaria Aldeneh, Takuya Higuchi, Jee-weon Jung +6
Self-supervised features are typically used in place of filter-bank features in speaker verification models. However, these models were originally designed to ingest filter-bank fe…
cs.SD2024
ESPnet-SPK: full pipeline speaker embedding toolkit with reproducible recipes, self-supervised front-ends, and off-the-shelf models
Jee-weon Jung, Wangyou Zhang, Jiatong Shi +5
This paper introduces ESPnet-SPK, a toolkit designed with several objectives for training speaker embedding extractors. First, we provide an open-source platform for researchers in…