31 citations · 122 across the 37 of their papers we have counts for
9 papers · 1 filter
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,…
Improving Audio Anomalies Recognition Using Temporal Convolutional Attention Network
Qiang Huang, Thomas Hain
Anomalous audio in speech recordings is often caused by speaker voice distortion, external noise, or even electric interferences. These obstacles have become a serious problem in s…
Unsupervised Acoustic Unit Representation Learning for Voice Conversion using WaveNet Auto-encoders
Mingjie Chen, Thomas Hain
Unsupervised representation learning of speech has been of keen interest in recent years, which is for example evident in the wide interest of the ZeroSpeech challenges. This work…
Exploration of Audio Quality Assessment and Anomaly Localisation Using Attention Models
Qiang Huang, Thomas Hain
Many applications of speech technology require more and more audio data. Automatic assessment of the quality of the collected recordings is important to ensure they meet the requir…
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…