Literature Review On Speech Recognition

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This paper provides a literature review of Speech Recognition, its background, methodologies and techniques used. Speech to Text or ASR involves processing the sound waves, extracting basic linguistic units or phonemes [1], then creating contextually correct and meaningful words to form a complete sentence. This paper explains types of speech, different approaches for speech recognition, techniques, the extraction of characteristics and the mathematical representationof ASR. Keywords
Speech Recognition, modules/phases of ASR, HMM, feature extraction, MEL, LPC, Large Vocabulary Continuous Speech Recognition-LVCSR, Pattern Classification techniques, Applications, tools

The most common and primary communication method
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It effects the complexity, processing requirements and accuracy of the recognition. There are no defined standards for size, the general perception is; small vocabulary - tens of words medium vocabulary - hundreds of words large vocabulary - thousands of words very-large vocabulary - tens of thousands of words. Types of Speech Recognition Systems
It can be categorized as follows; ISOLATED WORDS:
In this type of recognition, each word is surrounded by pause or break. It accepts single words or single utterance [3] at a time. These systems have "Listen/Not-Listen" states, where they require the speaker to wait between utterances (usually doing processing during the pauses) [2].

It’s similar to isolated words, but allow separate utterances to run together with minimal gaps between them.

Words run into each other and have to be segmented. [4]

It recognizes the natural speech. Such system is able to handle features of natural language as spontaneous speech may include mispronunciation, false starts and slang
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