8 citations · 25 across the 11 of their papers we have counts for
11 papers
NaviSense: A Multimodal Assistive Mobile application for Object Retrieval by Persons with Visual Impairment
Ajay Narayanan Sridhar, Fuli Qiao, Nelson Daniel Troncoso Aldas +4
People with visual impairments often face significant challenges in locating and retrieving objects in their surroundings. Existing assistive technologies present a trade-off: syst…
Swin-BERT: A Feature Fusion System designed for Speech-based Alzheimer's Dementia Detection
Yilin Pan, Yanpei Shi, Yijia Zhang +1
Speech is usually used for constructing an automatic Alzheimer's dementia (AD) detection system, as the acoustic and linguistic abilities show a decline in people living with AD at…
T-vectors: Weakly Supervised Speaker Identification Using Hierarchical Transformer Model
Yanpei Shi, Mingjie Chen, Qiang Huang +1
Identifying multiple speakers without knowing where a speaker's voice is in a recording is a challenging task. This paper proposes a hierarchical network with transformer encoders…
Towards Low-Resource StarGAN Voice Conversion using Weight Adaptive Instance Normalization
Mingjie Chen, Yanpei Shi, Thomas Hain
Many-to-many voice conversion with non-parallel training data has seen significant progress in recent years. StarGAN-based models have been interests of voice conversion. However,…
Speaker Re-identification with Speaker Dependent Speech Enhancement
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. Here sp…
Weakly Supervised Training of Hierarchical Attention Networks for Speaker Identification
Yanpei Shi, Qiang Huang, Thomas Hain
Identifying multiple speakers without knowing where a speaker's voice is in a recording is a challenging task. In this paper, a hierarchical attention network is proposed to solve…
Supervised Speaker Embedding De-Mixing in Two-Speaker Environment
Yanpei Shi, Thomas Hain
Separating different speaker properties from a multi-speaker environment is challenging. Instead of separating a two-speaker signal in signal space like speech source separation, a…
Robust Speaker Recognition Using Speech Enhancement And Attention Model
Yanpei Shi, Qiang Huang, Thomas Hain
In this paper, a novel architecture for speaker recognition is proposed by cascading speech enhancement and speaker processing. Its aim is to improve speaker recognition performanc…
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…