Abstract: This invention relates to a method, a device and a software application product for N-level quantization of vectors, wherein N is selectable prior to said quantization from a set of at least two pre-defined values that are smaller than or equal to a pre-defined maximum number of levels M. A reproduction vector for each vector is selected from an N-level codebook of N reproduction vectors that are, for each N in said set of at least two pre-defined values, represented by the first N reproduction vectors of the same joint codebook of M reproduction vectors. The invention further relates to a method, a device and a software application product for retrieving reproduction vectors for vectors that have been N-level quantized, to a system for transferring representations of vectors, to a method, a device and a software application product for determining a joint codebook, and to such a joint codebook itself.

Abstract: The invention relates to a support of a concatenative TTS synthesis. In order to generate a speech database as a basis for the TTS synthesis, first, a speech processing including a segmental parametric speech encoding of speech data based on a parametric modeling of speech is performed, which results in compressed parameterized speech segments. Then, the compressed parameterized speech segments are assembled in a speech database. In order to synthesize output speech, compressed parameterized speech segments are selected from the speech database based on an available text and decompressed to regain parameterized speech segments. The parameterized speech segments are then concatenated in a parameter domain. The output speech is synthesized based on these concatenated parametric speech segments.

Abstract: The present invention provides a new methodology for reusing codebooks for a multistage vector quantization of parameter quantizers of signals. Prior art multistage vector quantization is done in such a way that each stage has different optimized codebooks. The prior art codebooks, thus, use quite a lot of a memory storage space. Using the same codebook stages several times, according to the present invention, reduces the memory usage and a codebook structure maintains good quality by using optimized codebooks for the most important (first) stages in the quantization. The number of codebooks is reduced by reusing the same codebooks in the refining stages. Additionally, according to the present invention, using many predictors is space-wise efficient since they need only a few of coefficients instead of larger codebooks.

Abstract: A method and system for quantizing LSF vectors in a speech coder, wherein predicted LSF values based on previously decoded output values are used to estimate spectral distortion, along with the residual codebook vectors and the LSF coefficients. The method comprises the steps of obtaining a plurality of quantized LSF coefficients from the respective predicted LSF values and the residual codebook vectors; rearranging the quantized LSF coefficients in the frequency domain in an orderly fashion; obtaining the spectral distortion from the rearranged quantized LSF coefficients and the respective LSF coefficients; and an optimal code vector is selected based on the spectral distortion.

Abstract: The invention relates to a method for use in parametric speech coding. In order to enable an improved parametric coding of speech signals, the method comprises a first step of pre-processing a to be encoded speech based signal such that a phase structure of the to be encoded speech based signal is approached to a phase structure which is obtained when the to be encoded speech based signal is parametrically encoded and decoded again. Only in a second step, a parametric encoding is applied to this pre-processed to be encoded speech based signal. The invention relates equally to a corresponding device, to a corresponding coding module, to a corresponding system and to a corresponding software program product.

Abstract: A method and device for improving coding efficiency in audio coding. From the pitch values of a pitch contour of an audio signal, a plurality of simplified pitch contour segments are generated to approximate the pitch contour, based on one or more pre-selected criteria. The contour segments can be linear or non-linear with each contour segment represented by a first end point and a second end point. If the contour segments are linear, then only the information regarding the end points, instead of the pitch values, are provided to a decoder for reconstructing the audio signal. The contour segment can have a fixed maximum length or a variable length, but the deviation between a contour segment and the pitch values in that segment is limited by a maximum value.

Abstract: A method and device for use in conjunction with an encoder for encoding an audio signal into a plurality of parameters. Based on the behavior of the parameters, such as pitch, voicing, energy and spectral amplitude information of the audio signal, the audio signal can be segmented, so that the parameter update rate can be optimized. The parameters of the segmented audio signal are recorded in a storage medium or transmitted to a decoder so as to allow the decoder to reconstruct the audio signal based on the parameters indicative of the segment audio signals. For example, based on the pitch characteristic, the pitch contour can be approximated by a plurality of contour segments. An adaptive downsampling method is used to update the parameters based on the contour segments so as to reduce the update rate. At the decoder, the parameters are updated at the original rate.

Abstract: A method and system for quantizing LSF vectors in a speech coder, wherein predicted LSF values based on previously decoded output values are used to estimate spectral distortion, along with the residual codebook vectors and the LSF coefficients. The method comprises the steps of obtaining a plurality of quantized LSF coefficients from the respective predicted LSF values and the residual codebook vectors; rearranging the quantized LSF coefficients in the frequency domain in an orderly fashion; obtaining the spectral distortion from the rearranged quantized LSF coefficients and the respective LSF coefficients; and an optimal code vector is selected based on the spectral distortion.