271 citations · 429 across the 17 of their papers we have counts for
9 papers · 2 filters
The 2020 ESPnet update: new features, broadened applications, performance improvements, and future plans
Shinji Watanabe, Florian Boyer, Xuankai Chang +12
This paper describes the recent development of ESPnet (https://github.com/espnet/espnet), an end-to-end speech processing toolkit. This project was initiated in December 2017 to ma…
ESPnet-se: end-to-end speech enhancement and separation toolkit designed for asr integration
Chenda Li, Jing Shi, Wangyou Zhang +8
We present ESPnet-SE, which is designed for the quick development of speech enhancement and speech separation systems in a single framework, along with the optional downstream spee…
Recent Developments on ESPnet Toolkit Boosted by Conformer
Pengcheng Guo, Florian Boyer, Xuankai Chang +12
In this study, we present recent developments on ESPnet: End-to-End Speech Processing toolkit, which mainly involves a recently proposed architecture called Conformer, Convolution-…
Training Noisy Single-Channel Speech Separation With Noisy Oracle Sources: A Large Gap and A Small Step
Matthew Maciejewski, Jing Shi, Shinji Watanabe +1
As the performance of single-channel speech separation systems has improved, there has been a desire to move to more challenging conditions than the clean, near-field speech that i…
Multi-task Metric Learning for Text-independent Speaker Verification
Yafeng Chen, Wu Guo, Jingjing Shi +2
In this work, we introduce metric learning (ML) to enhance the deep embedding learning for text-independent speaker verification (SV). Specifically, the deep speaker embedding netw…
Exploring Universal Speech Attributes for Speaker Verification with an Improved Cross-stitch Network
Jiajun Qi, Wu Guo, Jingjing Shi +2
The universal speech attributes for x-vector based speaker verification (SV) are addressed in this paper. The manner and place of articulation form the fundamental speech attribute…