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Speech Features Extraction Techniques for Robust Emotional Speech Analysis/Recognition

机译:语音特征提取技术,用于健壮的情感语音分析/识别

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Speech is the most natural and convenient way of human communication. The speech represents not only a sequence of steady states of some sounds which are abruptly changing from one to another or a sound signal which can be ignored after perceiving or hearing it. But human Speech is a unique signal which carries and conveys multiple levels of knowledge source, linguistic and non-linguistic information. Speech signals are the information bearing signals which are evolved as functions of a single independent variable like time. Speech is a complex acoustic wave resulted as output of speaker’s effort. Speech serves to communicate from speaker to one or more listeners. The typical sound is called phone and it is produced when a phoneme is articulated. Most of Indian languages have 20-50 phonemes which constitute an alphabet of sounds to describe the different words in that language. Generally the speech is composed of sentences made of words. Usually words are composed of phoneme sequences called syllables. Speech analysis plays a vital role in speech recognition and synthesis. Speech analysis is also known as feature extraction or as speech signal front ends.
机译:语音是人类交流的最自然,最便捷的方式。语音不仅表示某些声音从一个突然变为另一个的稳态序列,或者代表在感知或听到声音之后可以忽略的声音信号。但是人类言语是一种独特的信号,它承载并传达了多种层次的知识来源,语言和非语言信息。语音信号是承载信息的信号,这些信号根据单个独立变量(例如时间)的函数而演变。语音是说话者努力输出的复杂声波。语音用于将说话者与一个或多个听众进行交流。典型的声音称为电话,是在发音音素时产生的。印度的大多数语言都有20-50个音素,这些音素构成了一个语音字母,用来描述该语言中的不同单词。通常,语音由单词构成的句子组成。通常,单词由称为音节的音素序列组成。语音分析在语音识别和合成中起着至关重要的作用。语音分析也称为特征提取或语音信号前端。

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