For the full list, please check this website.

• Mahapatra, A., Ulgen, I. R., Sisman, B. (2025) HuLA: Prosody-Aware Anti-Spoofing with Multi-task Learning for Expressive and Emotional Synthetic Speech. IEEE Transactions on Affective Computing. (submitted, Arxiv available)

• Ulgen, I. R., Du, Z., Lu, J., Koehn, P., Sisman, B (2025) Objective Evaluation of Speech Synthesis through Conditional Prediction of Discrete Tokens. IEEE Open Journal of Signal Processing. (submitted, Arxiv available)

• Ulgen, I. R., Chandra, S. S., Sisman, B (2025) Text-to-Speech for Unseen Speakers via Low-Complexity Discrete UnitBased Frame Selection. IEEE Open Journal of Signal Processing. (submitted, Arxiv available)

• Zhenqi, J., Rui, L., Sisman, B., Li, H. (2025) Multimodal Fine-grained Context Interaction Graph Modeling for Conversational Speech Synthesis. EMNLP 2025.

• Lam, P., Zhang, H., Chen, N. F., Sisman, B., & Herremans, D. (2025). PRESENT: Zero-Shot Text-to-Prosody Control. IEEE Signal Processing Letters.

• Mahapatra, A., Ulgen, I. R., Naini, A. R., Busso, C., & Sisman, B. (2025). Can Emotion Fool Anti-spoofing?. Interspeech 2025. 

• Chandra, S. S., Goncalves, L., Lu, J., Busso, C., & Sisman, B. (2025). EmotionRankCLAP: Bridging Natural Language Speaking Styles and Ordinal Speech Emotion via Rank-N-Contrast. Interspeech 2025. 

• Liu, R., Gao, P., Xi, J., Sisman, B., Busso, C., & Li, H. (2025). Towards Emotionally Consistent Text-Based Speech Editing: Introducing EmoCorrector and The ECD-TSE Dataset. Interspeech 2025.

• Naini, A. R., Goncalves, L., Salman, A. N., Mote, P., Ulgen, I. R., Thebaud, T., ... & Busso, C. (2025). The interspeech 2025 challenge on speech emotion recognition in naturalistic conditions. Interspeech 2025. 

• Rosero, K., Salman, A. N., Chandra, S., Sisman, B., Vant Slot, C., Kane, A. A., ... Busso, C. Advancing Pediatric ASR: The Role of Voice Generation in Disordered Speech. Interspeech 2025. 

• Liu, R., Sisman, B., Gao, G., & Li, H. (2024). Controllable accented text-to-speech synthesis with fine and coarse-grained intensity rendering. IEEE/ACM Transactions on Audio, Speech, and Language Processing.

• Goncalves, L., Leem, S. G., Lin, W. C., Sisman, B., & Busso, C. (2024). Versatile audio-visual learning for emotion recognition. IEEE Transactions on Affective Computing.

• Rajapakshe, T., Rana, R., Khalifa, S., Sisman, B., Schuller, B. W., & Busso, C. (2024). emodarts: Joint optimization of cnn & sequential neural network architectures for superior speech emotion recognition. IEEE Access.

• K. Zhou, B. Sisman, R. Rana, B. W. Schuller, and H. Li, “Emotion Intensity and its Control for Emotional Voice Conversion,” IEEE Transactions on Affective Computing, 1-18, 2022.

• R. Liu, B. Sisman, G. Gao and H. Li, “Decoding Knowledge Transfer for Neural Text-to-Speech Training,” in IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2022.

• B. Sisman, J. Yamagishi, S. King and H. Li, “An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning,” in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 132-157, 2021, doi: 10.1109/TASLP.2020.3038524.

• K. Zhou, B. Sisman, R. Liu, H. Li, “Emotional Voice Conversion: Theory, Databases and ESD” Speech Communication, 2021.

• R. Liu, B. Sisman, F. Bao, J. Yang, G. Gao and H. Li, “Exploiting Morphological and Phonological Features to Improve Prosodic Phrasing for Mongolian Speech Synthesis,” in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 274-285, 2021, doi: 10.1109/TASLP.2020.3040523.

• R. Liu, B. Sisman, Y. Lin, H. Li ‘FastTalker: A Neural Text-to-Speech Architecture with Shallow and Group Autoregression’ Neural Networks, 141, 306-314, 2021.

• R. Liu, B. Sisman, G. Gao and H. Li, “Expressive TTS Training With Frame and Style Reconstruction Loss,” in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 1806-1818, 2021, doi: 10.1109/TASLP.2021.3076369

• R. Liu, B. Sisman, F. Bao, G. Gao and H. Li, “Modeling Prosodic Phrasing With Multi-Task Learning in Tacotron-Based TTS,” in IEEE Signal Processing Letters, vol. 27, pp. 1470-1474, 2020, doi: 10.1109/LSP.2020.3016564.

• M. Zhang, B. Sisman, H.Li, ‘DBLSTM-based Voice Conversion with WaveNet Vocoder for Limited Parallel Data’ Speech Communication 122 (2020): 31-43.

• B. Sisman, M. Zhang and H. Li, “Group Sparse Representation With WaveNet Vocoder Adaptation for Spectrum and Prosody Conversion,” in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 6, pp. 1085-1097, June 2019, doi: 10.1109/TASLP.2019.2910637.

• Liu, R., Sisman, B., Schuller, B., Gao, G., Li, H. Accurate Emotion Strength Assessment for Seen and Unseen Speech Based on Data-Driven Deep Learning. Proc. Interspeech 2022, 5493-5497.

• Du, Z., Sisman, B., Zhou, K., Li, H. Disentanglement of Emotional Style and Speaker Identity for Expressive Voice Conversion. Proc. Interspeech 2022, 2603-2607.

• Lam, P., Zhang, H., Chen, N., Sisman, B. EPIC TTS Models: Empirical Pruning Investigations Characterizing Text-To-Speech Models. Proc. Interspeech 2022, 823-827.

• Lu J, Sisman B, Liu R, et al. VisualTTS: TTS with accurate lip-speech synchronization for automatic voice over[C]//ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022: 8032-8036.

• Z. Du, B. Sisman, K. Zhou, H. Li ‘Expressive Voice Conversion: A Joint Framework for Speaker Identity and Emotional Style Transfer’ ASRU 2021 – IEEE Automatic Speech Recognition and Understanding Workshop (ASRU).

• S. Nikonorov, B. Sisman M. Zhang, H. Li ‘DeepA: A Deep Neural Analyzer For Speech And Singing Vocoding’ ASRU 2021 – IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) 2021.

• K. Zhou, B. Sisman, R. Liu, H. Li ‘Limited Data Emotional Voice Conversion Leveraging Text-to-Speech: Two-stage Sequence-to-Sequence Training’ INTERSPEECH 2021.

• R. Liu, B. Sisman, H. Li ‘Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminability’ INTERSPEECH 2021.

• K. Zhou, B. Sisman, R. Liu and H. Li, “Seen and Unseen Emotional Style Transfer for Voice Conversion with A New Emotional Speech Dataset,” ICASSP 2021 – 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 920-924, doi: 10.1109/ICASSP39728.2021.9413391.

• R. Liu, B. Sisman and H. Li, “Graphspeech: Syntax-Aware Graph Attention Network for Neural Speech Synthesis,” ICASSP 2021 – 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 6059-6063, doi: 10.1109/ICASSP39728.2021.9413513.

• K. Zhou, B. Sisman and H. Li, “Vaw-Gan For Disentanglement And Recomposition Of Emotional Elements In Speech,” 2021 IEEE Spoken Language Technology Workshop (SLT), 2021, pp. 415-422, doi: 10.1109/SLT48900.2021.9383526.

• B. Sisman, J. Li, F. Bao, G. Gao and H. Li, “Teacher-Student Training For Robust Tacotron-Based TTS,” ICASSP 2020 – 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 6274-6278, doi: 10.1109/ICASSP40776.2020.9054681.

• Du Z, Zhou K, Sisman B, Li H. Spectrum and prosody conversion for cross-lingual voice conversion with cyclegan. In 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) 2020 Dec 7 (pp. 507-513). IEEE.

• Liu R, Sisman B, Bao F, et al. WaveTTS: Tacotron-based TTS with Joint Time-Frequency Domain Loss. Odyssey 2020 The Speaker and Language Recognition Workshop. 2020: 245-251.

• Zhang M, Sisman B, Zhao L, et al. Deepconversion: Voice conversion with limited parallel training data[J]. Speech Communication, 2020, 122: 31-43.

• Sisman B, Li H. Generative Adversarial Networks for Singing Voice Conversion with and without Parallel Data. In Odyssey 2020 (pp. 238-244).

• K. Zhou, B. Sisman, M. Zhang, H. Li, “Converting Anyone’s Emotion: Towards Speaker-Independent Emotional Voice Conversion”, INTERSPEECH 2020.

• K. Zhou, B. Sisman, H. Li, “Transforming Spectrum and Prosody for Emotional Voice Conversion with Non-parallel Data”, Speaker Odyssey 2020.

• B. Sisman, M. Zhang, M. Dong and H. Li, “On the Study of Generative Adversarial Networks for Cross-Lingual Voice Conversion,” 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2019, pp. 144-151, doi: 10.1109/ASRU46091.2019.9003939.

• B. Sisman, K. Vijayan, M. Dong and H. Li, “SINGAN: Singing Voice Conversion with Generative Adversarial Networks,” 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2019, pp. 112-118, doi: 10.1109/APSIPAASC47483.2019.9023162.

• Tjandra, B. Sisman, M. Zhang, S. Sakriani, H. Li, S. Nakamura, ‘VQVAE Unsupervised Unit Discovery and Multi-scale Code2Spec Inverter for Zerospeech Challenge 2019’ INTERSPEECH 2019.

• B. Sisman, M. Zhang and H. Li, “Group Sparse Representation With WaveNet Vocoder Adaptation for Spectrum and Prosody Conversion,” in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 6, pp. 1085-1097, June 2019, doi: 10.1109/TASLP.2019.2910637.

• Sisman, M. Zhang, S. Sakti, H. Li and S. Nakamura, “Adaptive Wavenet Vocoder for Residual Compensation in GAN-Based Voice Conversion,” 2018 IEEE Spoken Language Technology Workshop (SLT), 2018, pp. 282-289, doi: 10.1109/SLT.2018.8639507.

• Sisman, H. Li, ‘Limited Data Voice Conversion from Sparse Representation to GANs and WaveNet’, APSIPA ASC 2018 PhD Forum, Hawaii, Honolulu, United States [Best Presentation Award]

• Sisman, M. Zhang, H. Li, ‘A Voice Conversion Framework with Tandem Feature Sparse Representation and Speaker-Adapted WaveNet Vocoder’, INTERSPEECH 2018, India

• B. Sisman, H. Li, ‘Wavelet Analysis of Speaker Dependent and Independent Prosody for Voice Conversion’, INTERSPEECH 2018 

• B. Sisman, G. Lee, H. Li, ‘Phonetically Aware Exemplar-Based Prosody Transformation’, Speaker Odyssey, France, 2018

• M. Zhang, B. Sisman, S. S. Rallabandi, H. Li, L. Zhao, ‘Error Reduction Network for DBLSTM-based Voice Conversion’, APSIPA ASC 2018, Hawaii, Honolulu, United States

• J Xiao, S Yang, M. Zhang, B. Sisman, D. Huang, L Xie, M Dong, H Li, ‘The I2R-NWPU-NUS Text-to-Speech System for Blizzard Challenge 2018’, INTERSPEECH Blizzard Challenge 2018 Workshop

• Sisman, B. and Li, H., 2018. Wavelet Analysis of Speaker Dependent and Independent Prosody for Voice Conversion. Proc. Interspeech 2018, pp.52-56.

• B. Sisman, H. Li, K. C. Tan, “Transformation of prosody in voice conversion”, APSIPA ASC 2017, Kuala Lumpur, Malaysia

• B. Sisman, H. Li, K. C. Tan, “Sparse Representation of Phonetic Features for Voice Conversion with and without Parallel Data”, IEEE ASRU 2017, Okinawa, Japan