基于递归TDNN的神经网络文语转换
Text-To-Speech Conversion with Neural Networks: A Recurrent TDNN Approach
摘要：
本文描述了一个神经网络的设计，执行语音到声学映射的语音合成系统。时域神经网络架构的使用限制了在电话边界处发生的不连续性。循环数据输入还有助于平滑输出参数轨迹。独立测试表明，该系统产生的语音质量与现有商业文本到语音系统的语音相比毫不逊色。
英文摘要：
This paper describes the design of a neural network that performs the phonetic-to-acoustic mapping in a speech synthesis system. The use of a time-domain neural network architecture limits discontinuities that occur at phone boundaries. Recurrent data input also helps smooth the output parameter tracks. Independent testing has demonstrated that the voice quality produced by this system compares favorably with speech from existing commercial text-to-speech systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
