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.
|27||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|
|26||International Conference||Se-Yun Um, Sangshin Oh, Kyungguen Byun, Inseon Jang, ChungHyun Ahn, Hong-Goo Kang "Emotional Speech Synthesis with Rich and Granularized Control" in ICASSP, 2020|
|25||International Conference||Min-Jae Hwang, Eunwoo Song, Ryuichi Yamamoto, Frank Soong, Hong-Goo Kang "Improving LPCNet-based Text-to-Speech with Linear Prediction-structured Mixture Density Network" in ICASSP, 2020|
|24||International Conference||Hyeonjoo Kang, Young-Sun Joo, Inseon Jang, Chunghyun Ahn, Hong-Goo Kang "A Study on Acoustic Parameter Selection Strategies to Improve Deep Learning-Based Speech Synthesis" in APSIPA, 2019|
|23||International Conference||Min-Jae Hwang, Hong-Goo Kang "Parameter enhancement for MELP speech codec in noisy communication environment" in INTERSPEECH, 2019|
|22||International Conference||Keulbit Kim, Jinkyu Lee, Jan Skoglund, Hong-Goo Kang "Model Order Selection for Wind Noise Reduction in Non-negative Matrix Factorization" in ITC-CSCC, 2019|
|21||International Conference||Ohsung Kwon, Inseon Jang, ChungHyun Ahn, Hong-Goo Kang "Emotional Speech Synthesis Based on Style Embedded Tacotron2 Framework" in ITC-CSCC, 2019|
|20||International Conference||Kyungguen Byun, Eunwoo Song, Jinseob Kim, Jae-Min Kim, Hong-Goo Kang "Excitation-by-SampleRNN Model for Text-to-Speech" in ITC-CSCC, 2019|
|19||International Conference||Yang Yuan, Soo-Whan Chung, Hong-Goo Kang "Gradient-based active learning query strategy for end-to-end speech recognition" in ICASSP, 2019|
|18||International Conference||Soo-Whan Chung, Joon Son Chung, Hong-Goo Kang "Perfect match: Improved cross-modal embeddings for audio-visual synchronisation" in ICASSP, 2019|