| 1. | Back - up and restore your speech profile 备份和恢复您的语音特征资料 |
| 2. | Feature extraction based on wavelet transformation in speaker recognition 基于小波变换的说话人语音特征参数提取 |
| 3. | Fast wavelet analysis algorithm based on oblique projection and mellin transform 基于小波包变换的说话人语音特征参数的提取 |
| 4. | A robust feature - extraction method based on wavelet transform for text - independent speaker identification 变换的非特定人语音特征提取方法 |
| 5. | A comparative research on chinese children ' s implicit and explicit learning of english phonological traits 汉语儿童英语语音特征内隐与外显学习的比较研究 |
| 6. | The present paper makes an analysis of the character , the function , the cause and the phonetic characteristics of light tones 摘要对轻声的性质、轻声的功能、轻声的原因及轻声的语音特征进行了分析。 |
| 7. | An analysis of song qing - lings speech recording can prove her accent of chuansha and old shanghai counties 摘要通过对宋庆龄的讲话录音进行语音分析,可以说明在她的语音中有川沙语音和上海县城老派语音特征。 |
| 8. | The different which can represent a phoneme in different phonetic environments are called the allophones of that phoneme 音位是音系学研究的单位,是抽象的概念,每一个音位是一组语音特征的集合体,音位具有区别意义的作用。 |
| 9. | They include : 1 ) speech enhancement , 2 ) extracting robust speech features , 3 ) speech model compensation for noisy environments , 4 ) missing feature 目前的抗噪声技术主要分为四类:语音增强法、提取抗噪语音特征法、噪声补偿法、丢特征法。 |
| 10. | ( 4 ) in the thesis , the transformation of speech signals of different speaker is completed by bp neural network . the transformation of single word is completed ( 4 )本文利用bp神经网络来实现不同说话人语音特征的转换,基本上实现了单个词的语音特征的转换。 |