Abstract: Systems, methods, and computer program products for graphically displaying audio data are provided. In some implementations, a method is provided. The method includes displaying a graphical visual representation of digital audio data, the representation displaying a feature of the audio data on a feature axis with respect to time on a time axis. The method also includes receiving an input in the graphical visual representation selecting a range with respect to the feature and automatically extending the selected range with respect to time to define a selected region of the visual representation, where the extended range with respect to time is predefined and ignoring any component of the received input with respect to time.

Abstract: Audio data is processed and displayed in a series of spectral displays that progressively display the data at greater and greater resolution. Processing and displaying of the audio data is performed in a series of passes. For each pass, spectral data is generated from a portion of the audio data. The spectral data is cumulated and a display is rendered from the cumulated spectral data. This process is repeated until all of the passes have been completed.

Abstract: An invention for generating an enhanced DEPTH OF FIELD image from a set of images taken with the same point of view but different focus planes is disclosed. The enhanced DEPTH OF FIELD is generated irrespective of the order of images takes or number of images taken as long as the number of images is more than two. The input images will be processed, possibly center aligned, scaled to match one another exactly, then a sharpness image map is generated to represent the largest sharpness value of each pixel position and image index to indicate from which image, then a smooth process is performed to remove any artifacts possibly caused by bringing pixels from different images. Finally an enhanced DEPTH OF FIELD image is generated.

Abstract: A data compression system greatly compresses the stored data used by a speech recognition system employing hidden Markov models (HMM). The speech recognition system vector quantizes the acoustic space spoken by humans by dividing it into a predetermined number of acoustic features that are stored as codewords in a vector quantization (output probability) table or codebook. For each spoken word, the speech recognition system calculates an output probability value for each codeword, the output probability value representing an estimated probability that the word will be spoken using the acoustic feature associated with the codeword. The probability values are stored in an output probability table indexed by each codeword and by each word in a vocabulary. The output probability table is arranged to allow compression of the probability of values associated with each codeword based on other probability values associated with the same codeword, thereby compressing the stored output probability.

Abstract: A digital image processing system for convening continuous-tone images into halftone images to be output by a receiver with limited storage capacity. The continuous-tone image is converted into a first halftone image by threshold screening. Threshold screening involves comparing the pixel values of blocks of the continuous-tone image with cell values of a threshold array and turning on pixels of a first halftone image according to whether the pixel values of the continuous-tone block are greater than or equal to the cell values of the threshold array. The threshold array is associated with a plurality of gray patterns. A block count is determined which equals the number of pixels of each block of the first halftone image that are tuned on. A second halftone image is produced by combining gray patterns corresponding to the block counts. An error image is produced by determining differences between the first halftone image and the second halftone image. Scattered pixels in the error image are removed.