Improving LPCNet-based Text-to-Speech with Linear Prediction-structured Mixture Density Network
In this paper, we propose an improved LPCNet vocoder using a linear prediction (LP)-structured mixture density network (MDN).
The recently proposed LPCNet vocoder has successfully achieved high-quality and lightweight speech synthesis systems by combining a vocal tract LP filter with a WaveRNN-based vocal source (i.e., excitation) generator.
However, the quality of synthesized speech is often unstable because the vocal source component is insufficiently represented by the mu-law quantization method, and the model is trained without considering the entire speech production mechanism.
To address this problem, we first introduce LP-MDN, which enables the autoregressive neural vocoder to structurally represent the interactions between the vocal tract and vocal source components.
Then, we propose to incorporate the LP-MDN to the LPCNet vocoder by replacing the conventional discretized output with continuous density distribution.
The experimental results verify that the proposed system provides high quality synthetic speech by achieving a mean opinion score of 4.41 within a text-to-speech framework.
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|305||International Conference||Hyungseob Lim, Suhyeon Oh, Kyungguen Byun, Hong-Goo Kang "A Study on Conditional Features for a Flow-based Neural Vocoder" in Asilomar Conference on Signals, Systems, and Computers, 2020|
|304||International Conference||Soo-Whan Chung, Soyeon Choe, Joon Son Chung, Hong-Goo Kang "FaceFilter: Audio-visual speech separation using still images" in INTERSPEECH (*awarded Best Student Paper), 2020|
|303||International Conference||Soo-Whan Chung, Hong-Goo Kang, Joon Son Chung "Seeing Voices and Hearing Voices: Learning Discriminative Embeddings Using Cross-Modal Self-Supervision" in INTERSPEECH, 2020|
|302||International Conference||Hyewon Han, Soo-Whan Chung, Hong-Goo Kang "MIRNet: Learning multiple identities representations in overlapped speech" in INTERSPEECH, 2020|
|301||International Conference||Yoohwan Kwon, Soo-Whan Chung, Hong-Goo Kang "Intra-Class Variation Reduction of Speaker Representation in Disentanglement Framework" in INTERSPEECH, 2020|
|300||International Conference||Minh-Tri Ho, Jinyoung Lee, Bong-Ki Lee, Dong Hoon Yi, Hong-Goo Kang "A Cross-channel Attention-based Wave-U-Net for Multi-channel Speech Enhancement" in INTERSPEECH, 2020|
|299||International Journal||Young-Sun Joo, Hanbin Bae, Young-Ik Kim, Hoon-Young Cho, Hong-Goo Kang "Effective Emotion Transplantation in an End-to-End Text-to-Speech System" in IEEE Access, vol.8, pp.161713-161719, 2020|
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|297||Domestic Conference||오태양, 정기혁, 강홍구 "화자 및 발화 스타일 임베딩을 통한 다화자 음성합성 시스템 음질 향상" in 전자공학회 하계학술대회, pp.980-982, 2020|