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Code-excited linear prediction (CELP) is a linear predictive speech coding algorithm originally proposed by Manfred R. Schroeder and Bishnu S. Atal in 1985. At the time, it provided significantly better quality than existing low bit-rate algorithms, such as residual-excited linear prediction (RELP) and linear predictive coding (LPC) vocoders (e.g., FS-1015).
A linear encoder is a sensor, transducer or readhead paired with a scale that encodes position. The sensor reads the scale in order to convert the encoded position into an analog or digital signal , which can then be decoded into position by a digital readout (DRO) or motion controller.
Linear predictive coding (LPC) is a method used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model. [1] [2] LPC is the most widely used method in speech coding and speech synthesis.
Linear prediction is a mathematical operation where future values of a discrete-time signal are estimated as a linear function of previous samples. In digital signal processing , linear prediction is often called linear predictive coding (LPC) and can thus be viewed as a subset of filter theory .
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.
A convolutional encoder is a discrete linear time-invariant system. Every output of an encoder can be described by its own transfer function, which is closely related to the generator polynomial. An impulse response is connected with a transfer function through Z-transform. Transfer functions for the first (non-recursive) encoder are:
In particular, the most common speech coding scheme is the LPC-based code-excited linear prediction (CELP) coding, which is used for example in the GSM standard. In CELP, the modeling is divided in two stages, a linear predictive stage that models the spectral envelope and a code-book-based model of the residual of the linear predictive model.
From this construction, RM(r,m) is a binary linear block code (n, k, d) with length n = 2 m, dimension (,) = (,) + (,) and minimum distance = for . The dual code to RM( r,m ) is RM( m - r -1, m ). This shows that repetition and SPC codes are duals, biorthogonal and extended Hamming codes are duals and that codes with k = n /2 are self-dual.