Example apparatus to improve timestamp transition resolution of watermarks are disclosed. A disclosed example apparatus is to decode timestamps in respective ones of detected watermarks, estimate a first transition window indicative of a transition between a first time period to a second time period based on a first one of the timestamps and a second one of the timestamps, and when the first transition window does not satisfy a threshold, estimate a second transition window indicative of a transition between the second time period and a third time period based on the second one of the timestamps and a third one of the timestamps. The disclosed example apparatus is also to determine a first mapped transition window based on an intersection of the first transition window and the second transition window, and set the first mapped transition window as a reference time transition window for subsequent time periods.

Example apparatus to improve timestamp transition resolution of watermarks are disclosed. A disclosed example apparatus is to decode timestamps in respective ones of detected watermarks, estimate a first transition window indicative of a transition between a first time period to a second time period based on a first one of the timestamps and a second one of the timestamps, and when the first transition window does not satisfy a threshold, estimate a second transition window indicative of a transition between the second time period and a third time period based on the second one of the timestamps and a third one of the timestamps. The disclosed example apparatus is also to determine a first mapped transition window based on an intersection of the first transition window and the second transition window, and set the first mapped transition window as a reference time transition window for subsequent time periods.

Controlling a concealment method for a lost audio frame associated with a received audio signal is provided. At least one bin vector of a spectral representation for at least one tone is obtained, wherein the at least one bin vector includes three consecutive bin values for the at least one tone. Whether each of the three consecutive bin values has a complex value or a real value is determined. Responsive to the determination, the three consecutive bin values are processed to estimate a frequency of the at least one tone based on whether each bin value has a complex value or a real value.

Controlling a concealment method for a lost audio frame associated with a received audio signal is provided. At least one bin vector of a spectral representation for at least one tone is obtained, wherein the at least one bin vector includes three consecutive bin values for the at least one tone. Whether each of the three consecutive bin values has a complex value or a real value is determined. Responsive to the determination, the three consecutive bin values are processed to estimate a frequency of the at least one tone based on whether each bin value has a complex value or a real value.

A method for analyzing an acoustic signal having a time period and having a plurality of repeated audio patterns, has the following steps: receiving an audio signal having the acoustic signal; determining the audio patterns repeated within the acoustic signal; determining a window length for a plurality of windows, wherein the window length divides the time period of the acoustic signal into the plurality of windows; and windowing the acoustic signal to obtain the plurality of windows.

A computing system for a plurality of classes of audio events is provided, including one or more processors configured to divide a run-time audio signal into a plurality of segments and process each segment of the run-time audio signal in a time domain to generate a normalized time domain representation of each segment. The processor is further configured to feed the normalized time domain representation of each segment to an input layer of a trained neural network. The processor is further configured to generate, by the neural network, a plurality of predicted classification scores and associated probabilities for each class of audio event contained in each segment of the run-time input audio signal. In post-processing, the processor is further configured to generate smoothed predicted classification scores, associated smoothed probabilities, and class window confidence values for each class for each of a plurality of candidate window sizes.

A computing system for a plurality of classes of audio events is provided, including one or more processors configured to divide a run-time audio signal into a plurality of segments and process each segment of the run-time audio signal in a time domain to generate a normalized time domain representation of each segment. The processor is further configured to feed the normalized time domain representation of each segment to an input layer of a trained neural network. The processor is further configured to generate, by the neural network, a plurality of predicted classification scores and associated probabilities for each class of audio event contained in each segment of the run-time input audio signal. In post-processing, the processor is further configured to generate smoothed predicted classification scores, associated smoothed probabilities, and class window confidence values for each class for each of a plurality of candidate window sizes.

The invention provides an audio encoder for encoding an audio signal so as to produce therefrom an encoded signal, the audio encoder including: a framing device configured to extract frames from the audio signal; a quantizer configured to map spectral lines of a spectrum signal derived from the frame of the audio signal to quantization indices, wherein the quantizer has a dead-zone, in which the input spectral lines are mapped to quantization index zero; and a control device configured to modify the dead-zone; wherein the control device includes a tonality calculating device configured to calculate at least one tonality indicating value for at least one spectrum line or for at least one group of spectral lines, wherein the control device is configured to modify the dead-zone for the at least one spectrum line or the at least one group of spectrum lines depending on the respective tonality indicating value.

The invention provides an audio encoder for encoding an audio signal so as to produce therefrom an encoded signal, the audio encoder including: a framing device configured to extract frames from the audio signal; a quantizer configured to map spectral lines of a spectrum signal derived from the frame of the audio signal to quantization indices, wherein the quantizer has a dead-zone, in which the input spectral lines are mapped to quantization index zero; and a control device configured to modify the dead-zone; wherein the control device includes a tonality calculating device configured to calculate at least one tonality indicating value for at least one spectrum line or for at least one group of spectral lines, wherein the control device is configured to modify the dead-zone for the at least one spectrum line or the at least one group of spectrum lines depending on the respective tonality indicating value.

A computer-implemented method can include receiving a first signal corresponding to a first flow of acoustic energy, applying a transform to the received first signal using at least a first amplitude-independent window size at a first frequency and a second amplitude-independent window size at a second frequency, the second amplitude-independent window size improving a temporal response at the second frequency, wherein the second frequency is subject to amplitude reduction due to a resonance phenomenon associated with the first frequency, and storing a first encoded signal, the first encoded signal based on applying the transform to the received first signal.