Speech Enhancement

	Speech Enhancement Speech enhancement aims to improve speech quality by using various algorithms. The objective of enhancement is improvement in intelligibility and/or overall perceptual quality of degraded speech signal using audio signal processing techniques. Enhancing of speech degraded by noise, or noise reduction, is the most important field of speech enhancement, and used for many applications such as mobile phones, VoIP, teleconferencing systems, speech recognition, speaker diarization, and hearing aids. Algorithms The algorithms of speech enhancement for noise reduction can be categorized into three fundamental classes: filtering techniques, spectral restoration, and model-based methods.J. Benesty, M. M. Sondhi, Y. Huang (ed). ''Springer Handbook of Speech Processing''. pp.843-869. Springer, 2007. . * Filtering Techniques :* Spectral Subtraction Method :* Wiener Filtering :* Signal subspace approach (SSA) * Spectral Restoration :* Minimum Mean-Square-Error Short-Time Spectral Amplitu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Speech Speech is a human vocal communication using language. Each language uses Phonetics, phonetic combinations of vowel and consonant sounds that form the sound of its words (that is, all English words sound different from all French words, even if they are the same word, e.g., "role" or "hotel"), and using those words in their semantic character as words in the lexicon of a language according to the Syntax, syntactic constraints that Governance, govern lexical words' function in a sentence. In speaking, speakers perform many different intentional speech acts, e.g., informing, declaring, asking, persuading, directing, and can use Elocution, enunciation, Intonation (linguistics), intonation, degrees of loudness, tempo, and other non-representational or Paralanguage, paralinguistic aspects of vocalization to convey meaning. In their speech, speakers also unintentionally communicate many aspects of their social position such as sex, age, place of origin (through Accent (sociolinguistics ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Wiener Filtering In signal processing, the Wiener filter is a filter used to produce an estimate of a desired or target random process by linear time-invariant ( LTI) filtering of an observed noisy process, assuming known stationary signal and noise spectra, and additive noise. The Wiener filter minimizes the mean square error between the estimated random process and the desired process. Description The goal of the Wiener filter is to compute a statistical estimate of an unknown signal using a related signal as an input and filtering that known signal to produce the estimate as an output. For example, the known signal might consist of an unknown signal of interest that has been corrupted by additive noise. The Wiener filter can be used to filter out the noise from the corrupted signal to provide an estimate of the underlying signal of interest. The Wiener filter is based on a statistical approach, and a more statistical account of the theory is given in the minimum mean square error (MMSE) es ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Speech Recognition Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis. Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent". Speech recognition ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]