Knowledge-Based Speech Signal Representation

这项研究的目标是使用最近开发的自动优化过程来进一步设计基于语音特征的基于知识的语音信号表示，语音特征是语音信号的消息承载成分。基于知识的信号表示由声学参数组成，所述声学参数是对语音信号或其时频表示执行的精确测量，以针对语音信号中的语言信息。这样的表示可以用作语音识别系统的前端，或者可以用作那些难以产生自然发声语音(无论是由于言语障碍、听力损失还是学习第二语言)的人的语音训练。在HMM语音识别系统中，AP与传统倒谱参数的比较表明，AP能更好地从语音信号中提取语音相关信息，减少说话人依赖效应。在以前的研究中，AP是针对发音语音特征而设计的，利用声学语音知识和直方图分析来观察数据，这是一个耗时且主观的过程。相比之下，我们开发的优化程序是有效的，并使用了客观Fisher准则和分类树。此外，优化过程允许我们探索许多参数来确定最能表征语音特征的一个(S)，并将其与其反义词(S)区分开来。在语音识别系统中对手工设计的发音AP和优化后的发音AP进行了比较，结果表明两者具有可比性。在这个项目中，我们计划通过优化过程来完成基于知识的语音信号表示，以开发与发音语音特征的位置和剩余发音语音特征的方式相关的AP。

The goal of this study is to use a recently developed automatic optimization procedure to further the design of a knowledge based speech signal representation based on phonetic features, the message bearing components of the speech signal. The knowledge based signal representation consists of acoustic parameters that are exact measures performed on the speech signal or its time frequency representation to target the linguistic information in the speech signal. Such a representation can serve as the front end of a speech recognition system, or it can be used as a speech training for those having difficulty producing natural sounding speech (whether due to a speech impairment, hearing loss or learning of a second language). A comparison of the APs and the traditional cepstral based parameters in an HMM speech recognition system shows that the APs are better able to extract the phonetically relevant information from the speech signal and reduce speaker dependent effects. In previous research, APs were designed for the manner of articulation phonetic features using acoustic phonetic knowledge and histogram analysis to eye ball the data, a time consuming and subjective process. In contrast, the optimization procedure we developed is efficient and uses the objective Fisher criterion and classification trees. Furthermore, the optimization procedure allows us to explore many parameters to determine the one(s) that best characterizes a phonetic feature and separates it from its antonym(s). A comparison of the hand designed manner of articulation APs and the optimized ones in a speech recognition system shows that they yield comparable results. In this project, we plan to complete the knowledge based speech signal representation by using the optimization process to develop APs related to the place of articulation phonetic features and the remaining manner of articulation phonetic features.