Knowledge Commons of Institute of Automation,CAS
The Parameterized Phoneme Identity Feature as a Continuous Real-Valued Vector for Neural Network based Speech Synthesis | |
Wen ZQ(温正棋)![]() ![]() ![]() ![]() | |
2016-09 | |
会议名称 | Annual Conference of the International Speech Communication Association-Interspeech |
会议录名称 | INTERSPEECH |
会议日期 | Sep 8-12, 2016 |
会议地点 | San Francisco,USA |
摘要 | In the speech synthesis systems, the phoneme identity feature indicated as the pronunciation unit is influenced by external contexts like the neighboring words and phonemes. This paper proposes to encode such relatedness and parameterize the pronunciation of the phoneme identity feature as a continuous real-valued vector. The vector, composed by a phoneme embedded vector (PEV) and a word embedded vector (WEV), is applied to substitute the binary vector whose representation is one-hot. It is realized in the word embedding model with the joint training structure where the PEV and WEV are learned together. The effectiveness of the proposed technique was evaluated by comparing it with the binary vector in the bidirectional long short term memory recurrent neural network (BLSTM-RNN) based speech synthesis systems. Improvement on the quality of the synthesized speech has been achieved from the proposed system, which proves the effectiveness of replacing the binary vector with the continuous real-valued vector in describing the phoneme identity feature. |
关键词 | Phoneme Embedded Vector Word Embedding Speech Synthesis Blstm-rnn |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41089 |
专题 | 多模态人工智能系统全国重点实验室_智能交互 |
通讯作者 | Wen, Zhengqi |
推荐引用方式 GB/T 7714 | Wen ZQ,Li Y,Tao JH,et al. The Parameterized Phoneme Identity Feature as a Continuous Real-Valued Vector for Neural Network based Speech Synthesis[C],2016. |
条目包含的文件 | 条目无相关文件。 |
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