Search Results for author: Jen-Cheng Hou

Found 5 papers, 0 papers with code

Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks

no code implementations30 Mar 2017 Jen-Cheng Hou, Syu-Siang Wang, Ying-Hui Lai, Yu Tsao, Hsiu-Wen Chang, Hsin-Min Wang

Precisely speaking, the proposed AVDCNN model is structured as an audio-visual encoder-decoder network, in which audio and visual data are first processed using individual CNNs, and then fused into a joint network to generate enhanced speech (the primary task) and reconstructed images (the secondary task) at the output layer.

Multi-Task Learning Speech Enhancement

Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks

no code implementations1 Sep 2017 Jen-Cheng Hou, Syu-Siang Wang, Ying-Hui Lai, Yu Tsao, Hsiu-Wen Chang, Hsin-Min Wang

Precisely speaking, the proposed AVDCNN model is structured as an audio-visual encoder-decoder network, in which audio and visual data are first processed using individual CNNs, and then fused into a joint network to generate enhanced speech (the primary task) and reconstructed images (the secondary task) at the output layer.

Multi-Task Learning Speech Enhancement

Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings

no code implementations31 Oct 2022 I-Chun Chern, Kuo-Hsuan Hung, Yi-Ting Chen, Tassadaq Hussain, Mandar Gogate, Amir Hussain, Yu Tsao, Jen-Cheng Hou

In summary, our results confirm the effectiveness of our proposed model for the AVSS task with proper fine-tuning strategies, demonstrating that multi-modal self-supervised embeddings obtained from AV-HuBERT can be generalized to audio-visual regression tasks.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +6

Audio-Visual Speech Enhancement Using Self-supervised Learning to Improve Speech Intelligibility in Cochlear Implant Simulations

no code implementations15 Jul 2023 Richard Lee Lai, Jen-Cheng Hou, Mandar Gogate, Kia Dashtipour, Amir Hussain, Yu Tsao

The aim of this study is to explore the effectiveness of audio-visual speech enhancement (AVSE) in enhancing the intelligibility of vocoded speech in cochlear implant (CI) simulations.

Self-Supervised Learning Speech Enhancement

Deep Complex U-Net with Conformer for Audio-Visual Speech Enhancement

no code implementations20 Sep 2023 Shafique Ahmed, Chia-Wei Chen, Wenze Ren, Chin-Jou Li, Ernie Chu, Jun-Cheng Chen, Amir Hussain, Hsin-Min Wang, Yu Tsao, Jen-Cheng Hou

Recent studies have increasingly acknowledged the advantages of incorporating visual data into speech enhancement (SE) systems.

Speech Enhancement

Cannot find the paper you are looking for? You can Submit a new open access paper.