An apparatus for selecting one of a first encoding algorithm and a second encoding algorithm includes a filter configured to receive the audio signal, to reduce the amplitude of harmonics in the audio signal and to output a filtered version of the audio signal. First and second estimators are provided for estimating first and second quality measures in the form of SNRs of segmented SNRs associated with the first and second encoding algorithms without actually encoding and decoding the portion of the audio signal using the first and second encoding algorithms. A controller is provided for selecting the first encoding algorithm or the second encoding algorithm based on a comparison between the first quality measure and the second quality measure.

A method and apparatus for providing signal processing coefficients for processing an input signal at a predetermined signal processing sampling rate, wherein the input signal is received at an input signal sampling rate, the method comprising the steps of computing a correlation or covariance function based on the received input signal at the input signal sampling rate to provide correlation or covariance coefficients at the input signal sampling rate, re-sampling the computed correlation or covariance coefficients having the input signal sampling rate to provide correlation or covariance coefficients at the predetermined signal processing sampling rate, and calculating the signal processing coefficients based on the correlation or covariance coefficients at the predetermined signal processing sampling rate.

A method and apparatus for providing signal processing coefficients for processing an input signal at a predetermined signal processing sampling rate, wherein the input signal is received at an input signal sampling rate, the method comprising the steps of computing a correlation or covariance function based on the received input signal at the input signal sampling rate to provide correlation or covariance coefficients at the input signal sampling rate, re-sampling the computed correlation or covariance coefficients having the input signal sampling rate to provide correlation or covariance coefficients at the predetermined signal processing sampling rate, and calculating the signal processing coefficients based on the correlation or covariance coefficients at the predetermined signal processing sampling rate.

Systems and methods for detecting similar audio being received by separate voice activated electronic devices, and ignoring those commands, is described herein. In some embodiments, a voice activated electronic device may be activated by a wakeword that is output by the additional electronic device, such as a television or radio, may capture audio of sound subsequently following the wakeword, and may send audio data representing the sound to a backend system. Upon receipt, the backend system may, in parallel to performing automated speech recognition processing to the audio data, generate a sound profile of the audio data, and may compare that sound profile to sound profiles of recently received audio data and/or flagged sound profiles. If the generated sound profile is determined to match another sound profiles, then the automated speech recognition processing may be stopped, and the voice activated electronic device may be instructed to return to a keyword spotting mode. If the matching sound profile is not already stored in a database of known sound profiles, it can be stored for future comparisons.

Systems and methods for detecting similar audio being received by separate voice activated electronic devices, and ignoring those commands, is described herein. In some embodiments, a voice activated electronic device may be activated by a wakeword that is output by the additional electronic device, such as a television or radio, may capture audio of sound subsequently following the wakeword, and may send audio data representing the sound to a backend system. Upon receipt, the backend system may, in parallel to performing automated speech recognition processing to the audio data, generate a sound profile of the audio data, and may compare that sound profile to sound profiles of recently received audio data and/or flagged sound profiles. If the generated sound profile is determined to match another sound profiles, then the automated speech recognition processing may be stopped, and the voice activated electronic device may be instructed to return to a keyword spotting mode. If the matching sound profile is not already stored in a database of known sound profiles, it can be stored for future comparisons.

Proposed is a method and apparatus for determining a weighting function for quantizing a linear predictive coding (LPC) coefficient and having a low complexity. The weighting function determination apparatus may convert an LPC coefficient of a mid-subframe of an input signal to one of a immittance spectral frequency (ISF) coefficient and a line spectral frequency (LSF) coefficient, and may determine a weighting function associated with an importance of the ISF coefficient or the LSF coefficient based on the converted ISF coefficient or LSF coefficient.

Disclosed are a method and apparatus for encoding and decoding a high frequency for bandwidth extension. The method includes: estimating a weight; and generating a high frequency excitation signal by applying the weight between random noise and a decoded low frequency spectrum.

Disclosed are a method and apparatus for encoding and decoding a high frequency for bandwidth extension. The method includes: estimating a weight; and generating a high frequency excitation signal by applying the weight between random noise and a decoded low frequency spectrum.

Disclosed is a method of encoding and decoding an audio signal using linear predictive coding (LPC) and an encoder and a decoder that perform the method. The method of encoding an audio signal to be performed by the encoder includes identifying a time-domain audio signal block-wise, quantizing a linear prediction coefficient obtained from a block of the audio signal through the LPC, generating an envelope based on the quantized linear prediction coefficient, extracting a residual signal based on the envelope and a result of converting the block into a frequency domain, grouping the residual signal by each sub-band and determining a scale factor for quantizing the grouped residual signal, quantizing the residual signal using the scale factor, and converting the quantized residual signal and the quantized linear prediction coefficient into a bitstream and transmitting the bitstream to a decoder.

Disclosed is a method of encoding and decoding an audio signal using linear predictive coding (LPC) and an encoder and a decoder that perform the method. The method of encoding an audio signal to be performed by the encoder includes identifying a time-domain audio signal block-wise, quantizing a linear prediction coefficient obtained from a block of the audio signal through the LPC, generating an envelope based on the quantized linear prediction coefficient, extracting a residual signal based on the envelope and a result of converting the block into a frequency domain, grouping the residual signal by each sub-band and determining a scale factor for quantizing the grouped residual signal, quantizing the residual signal using the scale factor, and converting the quantized residual signal and the quantized linear prediction coefficient into a bitstream and transmitting the bitstream to a decoder.