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A Machine Learning Framework for Cognitive Impairment Screening from Speech with Multimodal Large Models. [PDF]
Bioengineering (Basel)Chen S +7 more
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Through Awareness to Action: Overcoming Gender Inequities in Academic Medicine and Nephrology. [PDF]
Kidney Int RepGuditi S +6 more
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Supervised Speaker Embedding De-Mixing in Two-Speaker Environment [PDF]
2021 IEEE Spoken Language Technology Workshop (SLT), 2021 Published at ...
Thomas Hain
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OpenFEAT: Improving Speaker Identification by Open-Set Few-Shot Embedding Adaptation With Transformer [PDF]
, 2022 Household speaker identification with few enrollment utterances is an important yet challenging problem, especially when household members share similar voice characteristics and room acoustics.
Andreas Stolcke, Eunjung Han
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On Deep Speaker Embeddings for Speaker Verification
2021 44th International Conference on Telecommunications and Signal Processing (TSP), 2021In recent years, there has been a tremendous application spike in the field of deep neural networks (DNN), including increasing interest in automatic speaker recognition systems development. Currently, the utilization of DNN-based speaker embeddings, such as x-vectors or d-vectors, is a common way of creating speaker-specific acoustic models. In recent
Maros Jakubec +3 more
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Graph-embedding for speaker recognition
Interspeech 2010, 2010This chapter presents applications of graph embedding to the problem of text-independent speaker recognition. Speaker recognition is a general term encompassing multiple applications. At the core is the problem of speaker comparison—given two speech recordings (utterances), produce a score which measures speaker similarity.
Zahi N. Karam, William M. Campbell
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