Subspace models for bottleneck features. - Jun Qi 002; Dong Wang 013; Javier Tejedor (INTERSPEECH, 2013)

Bottleneck features based on gammatone frequency cepstral coefficients. - Jun Qi 002; Dong Wang 013; Ji Xu; Javier Tejedor (INTERSPEECH, 2013)

Auditory features based on Gammatone filters for robust speech recognition. - Jun Qi 002; Dong Wang 013; Yi Jiang; Runsheng Liu (ISCAS, 2013)

Improving bottleneck features for automatic speech recognition using gammatone-based cochleagram and sparsity regularization. - Chao Ma; Jun Qi 002; Dongmei Li; Runsheng Liu (APSIPA, 2015)

Deep multi-view representation learning for multi-modal features of the schizophrenia and schizo-affective disorder. - Jun Qi 002; Javier Tejedor (ICASSP, 2016)

Robust submodular data partitioning for distributed speech recognition. - Jun Qi 002; Javier Tejedor (ICASSP, 2016)

Unsupervised Submodular Rank Aggregation on Score-based Permutations. - Jun Qi 002; Javier Tejedor (CoRR, 2017)

Distributed Submodular Maximization for Large Vocabulary Continuous Speech Recognition. - Jun Qi 002; Xu Liu 017; Shunsuke Kamijo; Javier Tejedor (ICASSP, 2018)

A Theory on Deep Neural Network Based Vector-to-Vector Regression With an Illustration of Its Expressive Power in Speech Enhancement. - Jun Qi 002; Jun Du 002; Sabato Marco Siniscalchi; Chin-Hui Lee 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2019)

Performance Analysis for Tensor-Train Decomposition to Deep Neural Network Based Vector-to-Vector Regression. - Jun Qi 002; Xiaoli Ma; Chin-Hui Lee 001; Jun Du 002; Sabato Marco Siniscalchi (CISS, 2020)

Tensor-To-Vector Regression for Multi-Channel Speech Enhancement Based on Tensor-Train Network. - Jun Qi 002; Hu Hu; Yannan Wang; Chao-Han Huck Yang; Sabato Marco Siniscalchi; Chin-Hui Lee 001 (ICASSP, 2020)

Submodular Rank Aggregation on Score-Based Permutations for Distributed Automatic Speech Recognition. - Jun Qi 002; Chao-Han Huck Yang; Javier Tejedor (ICASSP, 2020)

Characterizing Speech Adversarial Examples Using Self-Attention U-Net Enhancement. - Chao-Han Huck Yang; Jun Qi 002; Pin-Yu Chen; Xiaoli Ma; Chin-Hui Lee 001 (ICASSP, 2020)

Enhanced Adversarial Strategically-Timed Attacks Against Deep Reinforcement Learning. - Chao-Han Huck Yang; Jun Qi 002; Pin-Yu Chen; Yi Ouyang; I-Te Danny Hung; Chin-Hui Lee 001; Xiaoli Ma (ICASSP, 2020)

Exploring Deep Hybrid Tensor-to-Vector Network Architectures for Regression Based Speech Enhancement. - Jun Qi 002; Hu Hu; Yannan Wang; Chao-Han Huck Yang; Sabato Marco Siniscalchi; Chin-Hui Lee 001 (INTERSPEECH, 2020)

Variational Quantum Circuits for Deep Reinforcement Learning. - Samuel Yen-Chi Chen; Chao-Han Huck Yang; Jun Qi 002; Pin-Yu Chen; Xiaoli Ma; Hsi-Sheng Goan (IEEE Access, 2020)

Variational Inference-Based Dropout in Recurrent Neural Networks for Slot Filling in Spoken Language Understanding. - Jun Qi 002; Xu Liu 017; Javier Tejedor (CoRR, 2020)

On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression. - Jun Qi 002; Jun Du 002; Sabato Marco Siniscalchi; Xiaoli Ma; Chin-Hui Lee 001 (IEEE Signal Process. Lett., 2020)

Analyzing Upper Bounds on Mean Absolute Errors for Deep Neural Network-Based Vector-to-Vector Regression. - Jun Qi 002; Jun Du 002; Sabato Marco Siniscalchi; Xiaoli Ma; Chin-Hui Lee 001 (IEEE Trans. Signal Process., 2020)

Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition. - Chao-Han Huck Yang; Jun Qi 002; Samuel Yen-Chi Chen; Pin-Yu Chen; Sabato Marco Siniscalchi; Xiaoli Ma; Chin-Hui Lee 001 (ICASSP, 2021)

QTN-VQC: An End-to-End Learning framework for Quantum Neural Networks. - Jun Qi 002; Chao-Han Huck Yang; Pin-Yu Chen (CoRR, 2021)

Designing Tensor-Train Deep Neural Networks For Time-Varying MIMO Channel Estimation. - Jing Zhang 031; Xiaoli Ma; Jun Qi 002; Shi Jin 002 (IEEE J. Sel. Top. Signal Process., 2021)

Exploiting Hybrid Models of Tensor-Train Networks For Spoken Command Recognition. - Jun Qi 002; Javier Tejedor (ICASSP, 2022)

Classical-To-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networks. - Jun Qi 002; Javier Tejedor (ICASSP, 2022)

When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing. - Chao-Han Huck Yang; Jun Qi 002; Samuel Yen-Chi Chen; Yu Tsao 001; Pin-Yu Chen (ICASSP, 2022)

An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition. - Chao-Han Huck Yang; Jun Qi 002; Sabato Marco Siniscalchi; Chin-Hui Lee 001 (ISCSLP, 2022)

Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression. - Jun Qi 002; Chao-Han Huck Yang; Pin-Yu Chen; Min-Hsiu Hsieh (CoRR, 2022)

Theoretical Error Performance Analysis for Deep Neural Network Based Regression Functional Approximation. - Jun Qi 002 (2022)

Optimizing Quantum Federated Learning Based on Federated Quantum Natural Gradient Descent. - Jun Qi 002; Xiao-Lei Zhang 001; Javier Tejedor (ICASSP, 2023)

Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing. - Jun Qi 002; Chao-Han Huck Yang; Pin-Yu Chen; Javier Tejedor (IEEE ACM Trans. Audio Speech Lang. Process., 2023)

Mitigating Clipping Distortion in Multicarrier Transmissions Using Tensor-Train Deep Neural Networks. - Muhammad Shahmeer Omar; Jun Qi 002; Xiaoli Ma (IEEE Trans. Wirel. Commun., 2023)

Exploiting A Quantum Multiple Kernel Learning Approach For Low-Resource Spoken Command Recognition. - Xianyan Fu; Xiao-Lei Zhang 001; Chao-Han Huck Yang; Jun Qi 002 (ICASSP, 2024)

Leveraging Pre-Trained Neural Networks to Enhance Machine Learning with Variational Quantum Circuits. - Jun Qi 002; Chao-Han Huck Yang; Samuel Yen-Chi Chen; Pin-Yu Chen; Hector Zenil; Jesper Tegnér (CoRR, 2024)

Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learning. - Jun Qi 002; Chao-Han Yang; Samuel Yen-Chi Chen; Pin-Yu Chen (CoRR, 2024)

Interpretable Spectrum Transformation Attacks to Speaker Recognition Systems. - Jiadi Yao; Hong Luo; Jun Qi 002; Xiao-Lei Zhang 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2024)

Projection Valued-based Quantum Machine Learning Adapting to Differential Privacy Algorithm for Word-level Lipreading. - Hang Chen 001; Chang Wang; Jun Du 002; Chao-Han Huck Yang; Jun Qi 002 (ICASSP, 2025)

Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learning. - Jun Qi 002; Chao-Han Huck Yang; Samuel Yen-Chi Chen; Pin-Yu Chen (ISCAS, 2025)

VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning. - Jun Qi 002; Chao-Han Yang; Pin-Yu Chen; Min-Hsiu Hsieh (CoRR, 2025)

Joint Tensor-Train Parameterization for Efficient and Expressive Low-Rank Adaptation. - Jun Qi 002; Chen-Yu Liu; Sabato Marco Siniscalchi; Chao-Han Huck Yang; Min-Hsiu Hsieh (CoRR, 2025)