Abstract: Disclosed herein is a segmentation method, which divides an input audio stream into segments containing different homogeneous signals. The main objective of this method is localization of segments with stationary properties. This method seeks all no-stationary points or intervals in the audio stream and creates a list of segments. The obtained list of segments can be used as an input data for the following procedures, such as classification, speech/music/noise attribution and so on. The proposed segmentation method is based on the analysis of audio signal statistical features variation and comprises three main stages: stage of first-grade characteristics calculation, stage of second-grade characteristics calculation and stage of decision-making.

Abstract: A method of filtering digital audio data with short delay according to the present invention comprises the steps of: (a) buffering input source digital audio data; (b) calculating digital data that are being filtered from the buffered input source digital audio data; and (c) outputting a portion of the filtered digital data. The source digital audio data are sequence of digital samples. Buffer contents are shifted to arrange some of input samples in a buffer in the step (a). The step (b) comprises the steps of: (b-1) calculating a correlation matrix; (b-2) decomposing the correlation matrix; (b-3) calculating a filter matrix; and (b-4) calculating an approximation of the filtered digital data.

Abstract: The present invention relates to method and system for distinguishing speech from music in a digital audio signal in real time.

Abstract: Method for encoding and decoding a picture signal for detecting and correcting errors in a new structured GOB according to a data partition technique, method for encoding a picture signal, including the steps of (1) grouping picture information of one block group into respective information regions of each block, and partitioning to relevant regions, and (2) forming a partition table having length information of the partitioned regions of the grouped respective information regions.

Abstract: An iterative error-correction for decoding digital data transmitted or broadcasted is disclosed. The present invention is especially effective when there is high transmission noise and is applicable in decoding Turbo codes. The iterative decoding generally utilizes at least two parallel decoding processes and comprises two iterations from which the decoded data is obtained by combining decoded elements of the iterations. Also, for each iteration, an intermediate decoded data element is multiplied by a scaling factor based upon parameters of the previously decoded data element block and is used on the next decoding iteration. By utilizing at least two parallel decoding processes, the number of errors is significantly reduced and the decoding process may be optimally terminated.

Abstract: The present invention relates to method and system for distinguishing speech from music in a digital audio signal in real time.

Abstract: A method of filtering digital audio data with short delay according to the present invention comprises the steps of: (a) buffering input source digital audio data; (b) calculating digital data that are being filtered from the buffered input source digital audio data; and (c) outputting a portion of the filtered digital data. The source digital audio data are sequence of digital samples. Buffer contents are shifted to arrange some of input samples in a buffer in the step (a). The step (b) comprises the steps of: (b-1) calculating a correlation matrix; (b-2) decomposing the correlation matrix; (b-3) calculating a filter matrix; and (b-4) calculating an approximation of the filtered digital data.

Abstract: Disclosed herein is a segmentation method, which divides an input audio stream into segments containing different homogeneous signals. The main objective of this method is localization of segments with stationary properties. This method seeks all no-stationary points or intervals in the audio stream and creates a list of segments. The obtained list of segments can be used as an input data for the following procedures, such as classification, speech/music/noise attribution and so on. The proposed segmentation method is based on the analysis of audio signal statistical features variation and comprises three main stages: stage of first-grade characteristics calculation, stage of second-grade characteristics calculation and stage of decision-making.

Abstract: An apparatus and method for speech compression includes dividing the speech spectrum into a plurality of frames, assigning frame classifications to the plurality of frames, and determining the speech modeling parameters based on the assigned frame classification. The voiced part of the speech spectrum and the unvoiced part of the speech spectrum are synthesized separately using an Analysis by Synthesis allowing a correct correspondence between voiced and unvoiced parts of the reconstructed signal. Particularly, a frequency response of a special simulated signal based on the previous and current frames is used as an approximating function. The simulated signal is synthesized at the encoder side in the way it will be generated at the decoder side. Also, a better of two encoding methods is selected to encode the spectral magnitudes. A wavelet encoder and an inter-frame predictive encoder illustrate the invention's efficient, yet accurate reconstruction of synthesized digital speech.