One model to enhance them all: array geometry agnostic multi-channel personalized speech enhancement

no code implementations • 20 Oct 2021 • Hassan Taherian, Sefik Emre Eskimez, Takuya Yoshioka, Huaming Wang, Zhuo Chen, Xuedong Huang

Experimental results show that the proposed geometry agnostic model outperforms the model trained on a specific microphone array geometry in both speech quality and automatic speech recognition accuracy.

automatic-speech-recognition Speech Enhancement +2

Personalized Speech Enhancement: New Models and Comprehensive Evaluation

no code implementations • 18 Oct 2021 • Sefik Emre Eskimez, Takuya Yoshioka, Huaming Wang, Xiaofei Wang, Zhuo Chen, Xuedong Huang

Our results show that the proposed models can yield better speech recognition accuracy, speech intelligibility, and perceptual quality than the baseline models, and the multi-task training can alleviate the TSOS issue in addition to improving the speech recognition accuracy.

Speech Enhancement Speech Quality +1

Human Listening and Live Captioning: Multi-Task Training for Speech Enhancement

no code implementations • 5 Jun 2021 • Sefik Emre Eskimez, Xiaofei Wang, Min Tang, Hemin Yang, Zirun Zhu, Zhuo Chen, Huaming Wang, Takuya Yoshioka

Performance analysis is also carried out by changing the ASR model, the data used for the ASR-step, and the schedule of the two update steps.

automatic-speech-recognition Speech Enhancement +1

Advances in Online Audio-Visual Meeting Transcription

no code implementations • 10 Dec 2019 • Takuya Yoshioka, Igor Abramovski, Cem Aksoylar, Zhuo Chen, Moshe David, Dimitrios Dimitriadis, Yifan Gong, Ilya Gurvich, Xuedong Huang, Yan Huang, Aviv Hurvitz, Li Jiang, Sharon Koubi, Eyal Krupka, Ido Leichter, Changliang Liu, Partha Parthasarathy, Alon Vinnikov, Lingfeng Wu, Xiong Xiao, Wayne Xiong, Huaming Wang, Zhenghao Wang, Jun Zhang, Yong Zhao, Tianyan Zhou

This increases marginally to 1. 6% when 50% of the attendees are unknown to the system.

Speaker Diarization Speaker Identification +1

Attention-Aware Compositional Network for Person Re-identification

no code implementations • CVPR 2018 • Jing Xu, Rui Zhao, Feng Zhu, Huaming Wang, Wanli Ouyang

AACN consists of two main components: Pose-guided Part Attention (PPA) and Attention-aware Feature Composition (AFC).

Person Re-Identification Pose Estimation