Speech Processing

Speech processing is the study of speech signals and the processing methods of these signals. The signals are usually processed in a digital representation, so speech processing can be regarded as a special case of digital signal processing, applied to speech signal. Aspects of speech processing includes the acquisition, manipulation, storage, transfer and output of digital speech signals.

It is also closely tied to natural language processing (NLP), as its input can come from / output can go to NLP applications. E.g. text-to-speech synthesis may use a syntactic parser on its input text and speech recognition's output may be used by e.g. information extraction techniques. The main applications of speech processing are the recognition, synthesis and compression of human speech.

Speech processing includes the following areas of study:

• Speech recognition (also called voice recognition), which deals with analysis of the linguistic content of a speech signal and its conversion into a computer-readable format.
• Speaker recognition, where the aim is to recognize the identity of the speaker.
• Speech coding, a specialized form of data compression, is important in the telecommunication area.
• Voice analysis for medical purposes, such as analysis of vocal loading and dysfunction of the vocal cords.
• Speech synthesis: the artificial synthesis of speech, which usually means computer-generated speech. Advances in this area improve the computer's usability for the visually impaired.
• Speech enhancement: enhancing the intelligibility and/or perceptual quality of a speech signal, like audio noise reduction for audio signals.
• Speech compression is important in the telecommunications area for increasing the amount of information which can be transferred, stored, or heard, for a given set of time and space constraints.
• Speaker diarization is the process of determining who spoke when in a signal.