|
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] |
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] |
Speech Processing
Speech processing is the study of speech signals and the processing methods of 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 signals. Aspects of speech processing includes the acquisition, manipulation, storage, transfer and output of speech signals. The input is called speech recognition and the output is called speech synthesis. History Early attempts at speech processing and recognition were primarily focused on understanding a handful of simple phonetic elements such as vowels. In 1952, three researchers at Bell Labs, Stephen. Balashek, R. Biddulph, and K. H. Davis, developed a system that could recognize digits spoken by a single speaker. Pioneering works in field of speech recognition using analysis of its spectrum were reported in 1940s. Linear predictive coding (LPC), a speech processing algorithm, was first proposed by Fumitada Itakura of N ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Speech Interface Guideline
Speech interface guideline is a guideline with the aim for guiding decisions and criteria regarding designing interfaces operated by human voice. Speech interface system has many advantages such as consistent service and saving cost. However, for users, listening is a difficult task. It can become impossible when too many options are provided at once. This may mean that a user cannot intuitively reach a decision. To avoid this problem, limit options and a few clear choices the developer should consider such difficulties are usually provided. The guideline suggests the solution which is able to satisfy the users (customers). The goal of the guideline is to make an automated transaction at least as attractive and efficient as interacting with an attendant. Examples of common design guideline The following guideline is given by the Lucent Technologies (now Alcatel-Lucent USA) CONVERSANT System Version 6.0 Application Design Guidelines * Know Your Callers * Use Simple and Natural D ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Speech Coding
Speech coding is an application of data compression of digital audio signals containing speech. Speech coding uses speech-specific parameter estimation using audio signal processing techniques to model the speech signal, combined with generic data compression algorithms to represent the resulting modeled parameters in a compact bitstream. Some applications of speech coding are mobile telephony and voice over IP (VoIP). The most widely used speech coding technique in mobile telephony is linear predictive coding (LPC), while the most widely used in VoIP applications are the LPC and modified discrete cosine transform (MDCT) techniques. The techniques employed in speech coding are similar to those used in audio data compression and audio coding where knowledge in psychoacoustics is used to transmit only data that is relevant to the human auditory system. For example, in voiceband speech coding, only information in the frequency band 400 to 3500 Hz is transmitted but the reconst ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Audio Noise Reduction
Noise reduction is the process of removing noise from a signal. Noise reduction techniques exist for audio and images. Noise reduction algorithms may distort the signal to some degree. Noise rejection is the ability of a circuit to isolate an undesired signal component from the desired signal component, as with common-mode rejection ratio. All signal processing devices, both analog and digital, have traits that make them susceptible to noise. Noise can be random with an even frequency distribution (white noise), or frequency-dependent noise introduced by a device's mechanism or signal processing algorithms. In electronic systems, a major type of noise is ''hiss'' created by random electron motion due to thermal agitation. These agitated electrons rapidly add and subtract from the output signal and thus create detectable noise. In the case of photographic film and magnetic tape, noise (both visible and audible) is introduced due to the grain structure of the medium. In photograph ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Signal Subspace
In signal processing, signal subspace methods are empirical linear methods for dimensionality reduction and noise reduction. These approaches have attracted significant interest and investigation recently in the context of speech enhancement, speech modeling, and speech classification research. The signal subspace is also used in radio direction finding using the MUSIC (algorithm). Essentially the methods represent the application of a principal components analysis (PCA) approach to ensembles of observed time-series obtained by sampling, for example sampling an audio signal. Such samples can be viewed as vectors in a high-dimensional vector space over the real numbers. PCA is used to identify a set of orthogonal basis vectors (basis signals) which capture as much as possible of the energy in the ensemble of observed samples. The vector space spanned by the basis vectors identified by the analysis is then the ''signal subspace''. The underlying assumption is that information in spee ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hearing Aids
A hearing aid is a device designed to improve hearing by making sound audible to a person with hearing loss. Hearing aids are classified as medical devices in most countries, and regulated by the respective regulations. Small audio amplifiers such as personal sound amplification products (PSAPs) or other plain sound reinforcing systems cannot be sold as "hearing aids". Early devices, such as ear trumpets or ear horns, were passive amplification cones designed to gather sound energy and direct it into the ear canal. Modern devices are computerised electroacoustic systems that transform environmental sound to make it audible, according to audiometrical and cognitive rules. Modern devices also utilize sophisticated digital signal processing to try and improve speech intelligibility and comfort for the user. Such signal processing includes feedback management, wide dynamic range compression, directionality, frequency lowering, and noise reduction. Modern hearing aids require confi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Intelligibility (communication)
In speech communication, intelligibility is a measure of how comprehensible speech is in given conditions. Intelligibility is affected by the level (loud but not too loud) and quality of the speech signal, the type and level of background noise, reverberation (some reflections but not too many), and, for speech over communication devices, the properties of the communication system. A common standard measurement for the quality of the intelligibility of speech is the Speech Transmission Index (STI). The concept of speech intelligibility is relevant to several fields, including phonetics, human factors, acoustical engineering, and audiometry. Important Influences Speech is considered to be the major method of communication between humans. Humans alter the way they speak and hear according to many factors, like the age, gender, native language and social relationship between talker and listener. Speech intelligibility may also be affected by pathologies such as speech and hearing ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Speaker Diarization
Speaker diarisation ( or diarization) is the process of partitioning an audio stream containing human speech into homogeneous segments according to the identity of each speaker. It can enhance the readability of an automatic speech transcription by structuring the audio stream into speaker turns and, when used together with speaker recognition systems, by providing the speaker’s true identity. It is used to answer the question "who spoke when?" Speaker diarisation is a combination of speaker segmentation and speaker clustering. The first aims at finding speaker change points in an audio stream. The second aims at grouping together speech segments on the basis of speaker characteristics. With the increasing number of broadcasts, meeting recordings and voice mail collected every year, speaker diarisation has received much attention by the speech community, as is manifested by the specific evaluations devoted to it under the auspices of the National Institute of Standards and Techno ... [...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] |
