Abstract: A method for equalizing a speech signal generated within a pressurized air delivery system, the method including the steps of: generating an inhalation noise model (1152) based on inhalation noise; receiving an input signal (802) that includes a speech signal; and equalizing the speech signal (1156) based on the noise model.

Abstract: A speech communication system provides a speech encoder that generates a set of coded parameters representative of the desired speech signal characteristics. The speech communication system also provides a speech decoder that receives the set of coded parameters to generate reconstructed speech. The speech decoder includes an equalizer that computes a matching set of parameters from the reconstructed speech generated by the speech decoder, undoes the set of characteristics corresponding to the computed set of parameters, and imposes the set of characteristics corresponding to the coded set of parameters, thereby producing equalized reconstructed speech.

Abstract: A method of enhanced tandem communication is provided between at least a first portion of a network suitable for voice communications and a second portion of a network suitable for voice communications. During operation, two representations of an encoded signal are transmitted from the first portion of a network. The two representations comprise the encoded signal produced by a first codec and a parameter translation of the first encoded signal into an encoded signal compatible with a single common compressed voice codec (CCVC) format.

Abstract: A method for characterizing inhalation noise within a pressurized air delivery system, the method including the steps of: generating an inhalation noise model (912, 1012) based on inhalation noise; receiving an input signal (802) that includes inhalation noise comprising at least one inhalation noise burst; comparing (810) the input signal to the noise model to obtain a similarity measure; comparing the similarity measure to at least one threshold (832, 834) to detect the at least one inhalation noise burst; and characterizing (1354, 1356) the at least one detected inhalation noise burst.

Abstract: A method for detecting and attenuating inhalation noise in a communication system coupled to a pressurized air delivery system, the method including the steps of: generating an inhalation noise model (912, 1012) based on inhalation noise; receiving an input signal (802) that includes inhalation noise; comparing (810) the input signal to the noise model to obtain a similarity measure; determining (854) a gain factor based on the similarity measure; and modifying (852) the input signal based on the gain factor, wherein the inhalation noise in the input signal is attenuated based on the gain factor.

Abstract: A speech coder that performs analysis-by-synthesis coding of a signal determines gain parameters for each constituent component of multiple constituent components of a synthetic excitation signal. The speech coder generates a target vector based on an input signal. The speech coder further generates multiple constituent components associated with the synthetic excitation signal, wherein one constituent component of the multiple constituent components is based on a shifted version of another constituent component of the multiple constituent components. The speech coder further evaluates an error criteria based on the target vector and the multiple constituent components to determine a gain associated with each constituent component of the multiple constituent components.

Abstract: A system or method for modeling a signal, such as a speech signal, in which harmonic frequencies and amplitudes are identified and the harmonic magnitudes are interpolated to obtain spectral magnitudes at a set of fixed frequencies. An inverse transform is applied to the spectral magnitudes to obtain a pseudo auto-correlation sequence, from which linear prediction coefficients are calculated. From the linear prediction coefficients, model harmonic magnitudes are generated by sampling the spectral envelope defined by the linear prediction coefficients. A set of scale factors are then calculated as the ratio of the harmonic magnitudes to the model harmonic magnitudes and interpolated to obtain a second set of scale factors at the set of fixed frequencies. The spectral envelope magnitudes at the set of fixed frequencies are multiplied by the second set of scale factors to obtain new spectral magnitudes and the process is iterated to obtain final linear prediction coefficients.

Abstract: A method for equalizing a speech signal generated within a pressurized air delivery system, the method including the steps of: generating an inhalation noise model (1152) based on inhalation noise; receiving an input signal (802) that includes a speech signal; and equalizing the speech signal (1156) based on the noise model.

Abstract: A method for characterizing inhalation noise within a pressurized air delivery system, the method including the steps of: generating an inhalation noise model (912, 1012) based on inhalation noise; receiving an input signal (802) that includes inhalation noise comprising at least one inhalation noise burst; comparing (810) the input signal to the noise model to obtain a similarity measure; comparing the similarity measure to at least one threshold (832, 834) to detect the at least one inhalation noise burst; and characterizing (1354, 1356) the at least one detected inhalation noise burst.

Abstract: A method for detecting and attenuating inhalation noise in a communication system coupled to a pressurized air delivery system, the method including the steps of: generating an inhalation noise model (912, 1012) based on inhalation noise; receiving an input signal (802) that includes inhalation noise; comparing (810) the input signal to the noise model to obtain a similarity measure; determining (854) a gain factor based on the similarity measure; and modifying (852) the input signal based on the gain factor, wherein the inhalation noise in the input signal is attenuated based on the gain factor.

Abstract: A method and apparatus for prediction in a speech-coding system is provided herein. The method of a 1st order long-term predictor (LTP) filter, using a sub-sample resolution delay, is extended to a multi-tap LTP filter, or, viewed from another vantage point, the conventional integer-sample resolution multi-tap LTP filter is extended to use sub-sample resolution delay. This novel formulation of a multi-tap LTP filter offers a number of advantages over the prior-art LTP filter configurations. Particularly, defining the lag with sub-sample resolution makes it possible to explicitly model the delay values that have a fractional component, within the limits of resolution of the over-sampling factor used by the interpolation filter. The coefficients of such a multi-tap LTP filter are thus largely freed from modeling the effect of delays that have a fractional component.

Abstract: A method of enhanced tandem communication is provided between at least a first portion of a network suitable for voice communications and a second portion of a network suitable for voice communications. In an embodiment of the present invention, two representations of an encoded signal are transmitted from the first portion of a network, the encoded signal produced by a codec of the first portion of a network.

Abstract: The present invention provides a method of tandem communication between at least a first portion of a network suitable for voice communications and a second portion of a network suitable for voice communications. In an embodiment of the present invention, a common data format is applied to an encoded signal produced by a codec of the first portion of a network. Upon application, the common data format comprises quantised parameters of the encoded signal and descriptors characterising the coding scheme of the first codec.

Abstract: A speech coder that performs analysis-by-synthesis coding of a signal determines gain parameters for each constituent component of multiple constituent components of a synthetic excitation signal. The speech coder generates a target vector based on an input signal. The speech coder further generates multiple constituent components associated with the synthetic excitation signal, wherein one constituent component of the multiple constituent components is based on a shifted version of another constituent component of the multiple constituent components. The speech coder further evaluates an error criteria based on the target vector and the multiple constituent components to determine a gain associated with each constituent component of the multiple constituent components.

Abstract: A codebook excited linear prediction coding system providing improved digital speech coding for high quality speech at low bit rates with side-by-side codebooks for segments of the modeled input signal to reduce the complexity of the codebook search. A linear predictive filter responsive to an input signal desired to be modeled is used for identifying a basis vector from a first codebook over predetermined intervals as a subset of the input signal. A long term predictor and a vector quantizer provide synthetic excitation of modeled waveform signal components corresponding to the input signal desired to be modeled from side-by-side codebooks by providing codevectors with concatenated signals identified from the basis vector over the predetermined intervals with respect to the side-by-side codebooks. Once a codevector is identified, the codebook at the next segment is searched and a concatenation of codevectors is provided by selecting up to but not including the current segment.

Abstract: In a distributed speech recognition system comprising a first communication device which receives a speech input (34), encodes data representative of the speech input, and transmits the encoded data and a second remotely-located communication device which receives the encoded data and compares the encoded data with a known data set, the device including a processor with a program which controls the processor to operate according to a method of reconstructing the speech input including the step of receiving encoded data including encoded spectral data and encoded energy data. The method further includes the step of decoding the encoded spectral data and encoded energy data to determine the spectral data and energy data. The method also includes the step of combining the spectral data and energy data to reconstruct the speech input.

Abstract: A system or method for modeling a signal, such as a speech signal, in which harmonic frequencies and amplitudes are identified and the harmonic magnitudes are interpolated to obtain spectral magnitudes at a set of fixed frequencies. An inverse transform is applied to the spectral magnitudes to obtain a pseudo auto-correlation sequence, from which linear prediction coefficients are calculated. From the linear prediction coefficients, model harmonic magnitudes are generated by sampling the spectral envelope defined by the linear prediction coefficients. A set of scale factors are then calculated as the ratio of the harmonic magnitudes to the model harmonic magnitudes and interpolated to obtain a second set of scale factors at the set of fixed frequencies. The spectral envelope magnitudes at the set of fixed frequencies are multiplied by the second set of scale factors to obtain new spectral magnitudes and the process is iterated to obtain final linear prediction coefficients.

Abstract: In a distributed speech recognition system (20) comprising a first communication device (22) which receives a speech input (34), encodes data representative of the speech input (36, 38), and transmits the encoded data (42) and a second remotely-located communication device (26) which receives the encoded data (44) and compares the encoded data with a known data set, the device (26) including a processor (92) with a program which controls the processor (92) to operate according to a method of reconstructing the speech input including the step (44) of receiving encoded data including encoded spectral data and encoded energy data. The method further includes the step (46, 48) of decoding the encoded spectral data and encoded energy data to determine the spectral data and energy data. The method also includes the step (50, 52) of combining the spectral data and energy data to reconstruct the speech input.

Abstract: An input speech signal is encoded as one or more reflection coefficients. To reduce storage requirements, the reflection coefficients are scalar quantized by storing an N-bit code rather than the entire reflection coefficient. An exemplary value for N is 8. A table is provided having 2.sup.N reflection coefficient values. The N-bit code is used to look up reflection coefficient values from the table. To reduce spectral distortion due to scalar quantization, the reflection coefficient values in the table are non-linearly scaled.

Abstract: An improved speech coder provides a more natural sounding replication of speech by modifying the mean-squared error criterion for the selected speech coder parameters. Specifically, the modification emphasizes the signal components that the speech coder has difficulty matching, i.e. the high frequencies. This emphasis is constrained to certain limitations to avoid over-emphasizing the speech.