8 citations · 25 across the 11 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.CL2019★ 1 cited
H-VECTORS: Utterance-level Speaker Embedding Using A Hierarchical Attention Model
Yanpei Shi, Qiang Huang, Thomas Hain
In this paper, a hierarchical attention network to generate utterance-level embeddings (H-vectors) for speaker identification is proposed. Since different parts of an utterance may…
cs.CL2019★ 2 cited
Contextual Joint Factor Acoustic Embeddings
Yanpei Shi, Thomas Hain
Embedding acoustic information into fixed length representations is of interest for a whole range of applications in speech and audio technology. Two novel unsupervised approaches…
eess.AS2019★ 4 cited
Improving Noise Robustness In Speaker Identification Using A Two-Stage Attention Model
Yanpei Shi, Qiang Huang, Thomas Hain
While the use of deep neural networks has significantly boosted speaker recognition performance, it is still challenging to separate speakers in poor acoustic environments. To impr…