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Computer Science > Sound

Title: Multi-Level Attention Aggregation for Language-Agnostic Speaker Replication

Abstract: This paper explores the task of language-agnostic speaker replication, a novel endeavor that seeks to replicate a speaker's voice irrespective of the language they are speaking. Towards this end, we introduce a multi-level attention aggregation approach that systematically probes and amplifies various speaker-specific attributes in a hierarchical manner. Through rigorous evaluations across a wide range of scenarios including seen and unseen speakers conversing in seen and unseen lingua, we establish that our proposed model is able to achieve substantial speaker similarity, and is able to generalize to out-of-domain (OOD) cases.
Comments: Accepted to EACL Main 2024
Subjects: Sound (cs.SD); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2403.04111 [cs.SD]
  (or arXiv:2403.04111v2 [cs.SD] for this version)

Submission history

From: Yejin Jeon [view email]
[v1] Wed, 6 Mar 2024 23:47:48 GMT (582kb)
[v2] Wed, 3 Apr 2024 07:40:54 GMT (499kb)

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