31 citations · 122 across the 37 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
Latent Dirichlet Allocation Based Acoustic Data Selection for Automatic Speech Recognition
Mortaza, Doulaty, Thomas Hain
Selecting in-domain data from a large pool of diverse and out-of-domain data is a non-trivial problem. In most cases simply using all of the available data will lead to sub-optimal…