Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a modified analytics prediction machine learning model using an iterative transfer learning approach. For example, the disclosed systems generate an initial version of an analytics prediction machine learning model for predicting an analytics metric according to learned parameters. In some embodiments, the disclosed systems determine expected data channel contributions for the analytics metric according to prior data. Additionally, in some cases, the disclosed systems generate a modified analytics prediction machine learning model by iteratively updating model parameters such that predicted data channel contributions are within a threshold similarity of expected data channel contributions.

Abstract: A method and an apparatus for detecting an audio signal according to frequency domain energy is presented. The method may include receiving an audio signal frame; acquiring frequency domain energy distribution of the audio signal frame; obtaining a maximum value distribution characteristic of a frequency domain energy distribution derivative of the audio signal frame according to the frequency domain energy distribution of the audio signal frame; using the audio signal frame and each frame in a preset neighborhood range of the audio signal frame as a frame set, where the frame set includes a to-be-detected frame; and detecting the to-be-detected frame according to a maximum value distribution characteristic of a frequency domain energy distribution derivative of the frame set. In the various embodiments, detection on an audio signal can be implemented.

Abstract: A noise detection method and apparatus are disclosed. The noise detection method includes: obtaining a frequency-domain energy distribution parameter of a current frame of an audio signal, and obtaining a frequency-domain energy distribution parameter; obtaining a tone parameter of the current frame, and obtaining a tone parameter; determining, according to the tone parameter of the current frame and the tone parameter of each of the frames in the preset neighboring domain range of the current frame, whether the current frame is in a speech section or a non-speech section; and determining that the current frame is speech-grade noise if the current frame is in a speech section and a quantity of frequency-domain energy distribution parameters falling within a preset speech-grade noise frequency-domain energy distribution parameter interval in all the frequency-domain energy distribution parameters is greater than or equal to a first threshold.

Abstract: A noise detection method and apparatus are disclosed. The noise detection method includes: obtaining a frequency-domain energy distribution parameter of a current frame of an audio signal, and obtaining a frequency-domain energy distribution parameter; obtaining a tone parameter of the current frame, and obtaining a tone parameter; determining, according to the tone parameter of the current frame and the tone parameter of each of the frames in the preset neighboring domain range of the current frame, whether the current frame is in a speech section or a non-speech section; and determining that the current frame is speech-grade noise if the current frame is in a speech section and a quantity of frequency-domain energy distribution parameters falling within a preset speech-grade noise frequency-domain energy distribution parameter interval in all the frequency-domain energy distribution parameters is greater than or equal to a first threshold.

Abstract: A method and an apparatus for detecting an audio signal according to frequency domain energy is presented. The method may include receiving an audio signal frame; acquiring frequency domain energy distribution of the audio signal frame; obtaining a maximum value distribution characteristic of a frequency domain energy distribution derivative of the audio signal frame according to the frequency domain energy distribution of the audio signal frame; using the audio signal frame and each frame in a preset neighborhood range of the audio signal frame as a frame set, where the frame set includes a to-be-detected frame; and detecting the to-be-detected frame according to a maximum value distribution characteristic of a frequency domain energy distribution derivative of the frame set. In the various embodiments, detection on an audio signal can be implemented.

Abstract: A method and an apparatus for processing a speech signal according to frequency-domain energy where the method and apparatus include receiving an original speech signal including a first speech frame and a second speech frame that are adjacent to each other, performing a Fourier transform on the first speech frame and the second speech frame, obtaining a frequency-domain energy distribution of the first speech frame and the second speech frame, obtaining a frequency-domain energy correlation coefficient, and segmenting the original speech signal according to the frequency-domain energy correlation coefficient. Hence a problem that a speech signal segmentation result has low accuracy due to a characteristic of a phoneme of a speech signal or severe impact of noise when refined speech signal segmentation is performed may be resolved.

Abstract: The invention discloses a method including: performing in a unit of first timeframe frame length, framing on a continuous voice sample to obtain a plurality of first timeframes, detecting energy of each of the first timeframes, and determining a target first timeframe including a potential abrupt exception of a voice signal by analyzing a relationship between the energy of the plurality of first timeframes; performing, in a unit of second timeframe frame length, framing on the continuous voice sample to obtain a plurality of second timeframes, and processing each of the second timeframes to acquire a tone feature, and determining, by analyzing a tone feature of at least one of the second timeframes including at least one target second timeframe, whether the potential abrupt exception of a voice signal included in the target first timeframe included in the target second timeframe is a real abrupt exception of a voice signal.

Abstract: The invention discloses a method including: performing in a unit of first timeframe frame length, framing on a continuous voice sample to obtain a plurality of first timeframes, detecting energy of each of the first timeframes, and determining a target first timeframe including a potential abrupt exception of a voice signal by analyzing a relationship between the energy of the plurality of first timeframes; performing, in a unit of second timeframe frame length, framing on the continuous voice sample to obtain a plurality of second timeframes, and processing each of the second timeframes to acquire a tone feature, and determining, by analyzing a tone feature of at least one of the second timeframes including at least one target second timeframe, whether the potential abrupt exception of a voice signal included in the target first timeframe included in the target second timeframe is a real abrupt exception of a voice signal.

Abstract: A voice quality monitoring method and apparatus are provided, which solves a difficult problem of how to perform proper voice quality monitoring on a relatively long audio signal by using relatively low costs. The method includes capturing one or more voice signal segments from an input signal; performing voice segment segmentation on each voice signal segment to obtain one or more voice segments; and performing a voice quality evaluation on the voice segment to obtain a quality evaluation result according to the voice quality evaluation. Because the segmented voice segment includes only a voice signal and is shorter than the input signal, proper voice quality monitoring can be performed on a relatively long audio signal by using relatively low costs, thereby obtaining a more accurate voice quality evaluation result.

Abstract: The present invention discloses a method and a device for audio signal classification, and relates to the field of communications technologies, which solve a problem of high complexity of type classification of audio signals in the prior art. In the present invention, after an audio signal to be classified is received, a tonal characteristic parameter of the audio signal to be classified, where the tonal characteristic parameter of the audio signal to be classified is in at least one sub-band, is obtained, and a type of the audio signal to be classified is determined according to the obtained characteristic parameter. The present invention is mainly applied to an audio signal classification scenario, and implements audio signal classification through a relatively simple method.

Abstract: A decoding method and device are provided. The spectrum parameter of a current bad data frame is determined. Specifically, a number of continuous bad frames that occur currently is determined. A spectrum parameter of a good data frame before the current bad data frame is determined. And a constant mean value of a spectrum parameter is determined. Then, the spectrum parameter of the good data frame is adaptively shifted towards the constant mean value of the spectrum parameter according to the number of the continuous bad data frames to calculate and obtain spectrum parameter information of the current bad frame. When the continuous bad data frames occur, the relevance between the spectrum parameter of the nearest good frame and the spectrum parameter of the current bad frame is gradually reduced, so that more accurate spectrum parameter of the current bad data frame can be obtained, thereby obtaining a better speech quality under a same code rate and a same frame error rate.

Abstract: A frame compensation method is provided. The method includes: obtaining a length of a lost frame and a length of a correct frame; determining that the length of the correct frame is integral power of 2 times of the length of the lost frame, and then obtaining a data sequence with the same length as the length of the lost frame according to the correct frame; and compensating the lost frame according to the data sequence to obtain a compensated data frame. A frame compensation system is also provided. Lost frames in various formats are compensated according to correct frames in various formats, so that the limitation of the related art that a lost frame in a single format can be merely compensated according to a correct frame in a single format is eliminated, and the effect of the compensated data frames is better than that of filling comfort noises.

Abstract: The present invention discloses a method for performing a frame erasure concealment to a higher-band signal, including: calculating a periodic intensity of a higher-band signal with respect to a lower-band signal; judging whether the periodic intensity of the higher-band signal is higher than or equal to a preconfigured threshold; if the periodic intensity of the higher-band signal is higher than or equal to the preconfigured threshold, using a pitch period repetition method to perform the frame erasure concealment to the higher-band signal of a current lost frame; and if the periodic intensity of the higher-band signal is lower than the preconfigured threshold, using a previous frame data repetition method to perform the frame erasure concealment to the higher-band signal of the current lost frame. The present invention further discloses a device for performing a frame erasure concealment to a higher-band signal and a speech decoder. The problem that the quality of the voice signal is lowered is avoided.

Abstract: The present disclosure relates to a decoding method and apparatus. The method includes: receiving data frames from the coder; if any erroneous frame appears, calculating a pitch lag parameter of the erroneous frame; decoding the data frames according to the calculated pitch lag parameter of the erroneous frame, and obtaining decoded data. The process of determining the pitch lag parameter includes: determining the number of continuous erroneous frames and the pitch lag parameter of the previous frame; adjusting the pitch lag parameter of the previous frame according to the number of the continuous erroneous frames and a preset adjustment policy, and calculating and determining the pitch lag parameter of a current erroneous frame, wherein the preset adjustment policy is adjusting the determined pitch lag parameter of the current erroneous frame within a preset value range according to the number of the continuous erroneous frames.

Abstract: The present invention discloses a method and a device for audio signal classification, and relates to the field of communications technologies, which solve a problem of high complexity of type classification of audio signals in the prior art. In the present invention, after an audio signal to be classified is received, a tonal characteristic parameter of the audio signal to be classified, where the tonal characteristic parameter of the audio signal to be classified is in at least one sub-band, is obtained, and a type of the audio signal to be classified is determined according to the obtained characteristic parameter. The present invention is mainly applied to an audio signal classification scenario, and implements audio signal classification through a relatively simple method.

Abstract: An method for encoding comprising: obtaining, according to a data length of a first overlapped portion between encoding data of a current frame and encoding data of a previous frame, first encoding data corresponding to the data length of the first overlapped portion from the previous frame, if the previous frame is encoded in a first encoding mode and the current frame is to be encoded in a second encoding mode; and encoding, in the second encoding mode, the first encoding data corresponding to the data length of the first overlapped portion from the previous frame and encoding data of the current frame. The corresponding decoding method, encoding and decoding apparatuses are also disclosed.

Abstract: A frame compensation method is provided. The method includes: obtaining a length of a lost frame and a length of a correct frame; determining that the length of the correct frame is integral power of 2 times of the length of the lost frame, and then obtaining a data sequence with the same length as the length of the lost frame according to the correct frame; and compensating the lost frame according to the data sequence to obtain a compensated data frame. A frame compensation system is also provided. Lost frames in various formats are compensated according to correct frames in various formats, so that the limitation of the related art that a lost frame in a single format can be merely compensated according to a correct frame in a single format is eliminated, and the effect of the compensated data frames is better than that of filling comfort noises.

Abstract: The present disclosure relates to a decoding method and apparatus. The method includes: receiving data frames from the coder; if any erroneous frame appears, calculating a pitch lag parameter of the erroneous frame; decoding the data frames according to the calculated pitch lag parameter of the erroneous frame, and obtaining decoded data. The process of determining the pitch lag parameter includes: determining the number of continuous erroneous frames and the pitch lag parameter of the previous frame; adjusting the pitch lag parameter of the previous frame according to the number of the continuous erroneous frames and a preset adjustment policy, and calculating and determining the pitch lag parameter of a current erroneous frame, wherein the preset adjustment policy is adjusting the determined pitch lag parameter of the current erroneous frame within a preset value range according to the number of the continuous erroneous frames.

Abstract: A decoding method and device are provided. The spectrum parameter of a current bad data frame is determined. Specifically, a number of continuous bad frames that occur currently is determined. A spectrum parameter of a good data frame before the current bad data frame is determined. And a constant mean value of a spectrum parameter is determined. Then, the spectrum parameter of the good data frame is adaptively shifted towards the constant mean value of the spectrum parameter according to the number of the continuous bad data frames to calculate and obtain spectrum parameter information of the current bad frame. When the continuous bad data frames occur, the relevance between the spectrum parameter of the nearest good frame and the spectrum parameter of the current bad frame is gradually reduced, so that more accurate spectrum parameter of the current bad data frame can be obtained, thereby obtaining a better speech quality under a same code rate and a same frame error rate.

Abstract: A method for performing a frame erasure concealment for a higher-band signal involves calculating a periodic intensity of the higher-band signal with respect to pitch period information of a lower-band signal; comparing the periodic intensity to a preconfigured threshold and, if the periodic intensity is greater or equal to the preconfigured threshold, performing the frame erasure concealment with a pitch period repetition based method. If the periodic intensity is less than the preconfigured threshold, performing the frame erasure concealment with a previous frame data repetition based method. A device for performing a frame erasure concealment includes a periodic intensity calculation module, a pitch period repetition module, and a previous frame data repetition module.