Abstract:
The present application relates to the field of computer technologies, and in particular, to a stop word identification method used in an information retrieval system. In a stop word identification method, after a first query input by a user is acquired, a second query that belongs to a same session as the first query is acquired, and a stop word in the first query is identified according to a change-based feature of each word in the first query relative to the second query. According to the solution provided by the present application, a stop word in a query can be identified more accurately, and efficiency and precision of an information retrieval system are improved.
Abstract:
Present disclosure provide a linear prediction-based noise signal processing method includes: acquiring a noise signal, and obtaining a linear prediction coefficient according to the noise signal; filtering the noise signal according to the linear prediction coefficient, to obtain a linear prediction residual signal; obtaining a spectral envelope of the linear prediction residual signal according to the linear prediction residual signal; and encoding the spectral envelope of the linear prediction residual signal. According to the noise processing method, the noise generation method, the encoder, the decoder, and the encoding and decoding system that are in the embodiments of the present disclosure, more spectral details of an original background noise signal can be recovered, so that comfort noise can be closer to original background noise in terms of subjective auditory perception of a user, and subjective perception quality of the user is improved.
Abstract:
A voice activity detection (VAD) apparatus configured to provide a voice activity detection decision for an input audio signal. The VAD apparatus includes a state detector and a voice activity calculator. The state detector is configured to determine, based on the input audio signal, a current working state of the VAD apparatus among at least two different working states. Each of the at least two different working states is associated with a corresponding working state parameter decision set which includes at least one voice activity detection parameter. The voice activity calculator is configured to calculate a voice activity detection parameter value for the at least one voice activity detection parameter of the working state parameter decision set associated with the current working state, and to provide the voice activity detection decision by comparing the calculated voice activity detection parameter value with a threshold.
Abstract:
A method for processing an audio signal includes receiving a bitstream corresponding to the audio signal; obtaining a silence insertion descriptor (SID) type of a current frame of the audio signal by decoding the bitstream; obtaining a low-band parameter of the current frame by decoding the bitstream; obtaining a low-band signal of the current frame based on the low-band parameter; obtaining, based on the SID type of the current frame, a high-band parameter of the current frame; obtaining a high-band signal of the current frame based on the high-band parameter; and obtaining a synthesis signal of the current frame based on the low-band signal and the high-band signal.
Abstract:
A method for processing an audio signal includes receiving a bitstream corresponding to the audio signal; obtaining a silence insertion descriptor (SID) type of a current frame of the audio signal by decoding the bitstream; obtaining a low-band parameter of the current frame by decoding the bitstream; obtaining a low-band signal of the current frame based on the low-band parameter; obtaining, based on the SID type of the current frame, a high-band parameter of the current frame; obtaining a high-band signal of the current frame based on the high-band parameter; and obtaining a synthesis signal of the current frame based on the low-band signal and the high-band signal.
Abstract:
The present disclosure discloses an audio encoding and decoding method and an audio encoder and decoder. The audio encoding method includes: obtaining a current frame of an audio signal, where the current frame includes a high frequency band signal and a low frequency band signal; obtaining a first encoding parameter based on the high frequency band signal and the low frequency band signal; obtaining a second encoding parameter of the current frame based on the high frequency band signal, where the second encoding parameter includes tone component information; and performing bitstream multiplexing on the first encoding parameter and the second encoding parameter, to obtain an encoded bitstream.
Abstract:
A data processing apparatus and method are provided. The method includes: performing multi-level IR decomposition on original application code, extracting more abundant computation and data flow features to obtain an initial computational graph, and performing graph transformation processing on the initial computational graph to obtain a target computational graph, allowing an application corresponding to original application code to run in different systems and implement performance portability.
Abstract:
A method for processing an audio signal includes receiving a bitstream corresponding to the audio signal; obtaining a silence insertion descriptor (SID) type of a current frame of the audio signal by decoding the bitstream; obtaining a low-band parameter of the current frame by decoding the bitstream; obtaining a low-band signal of the current frame based on the low-band parameter; obtaining, based on the SID type of the current frame, a high-band parameter of the current frame; obtaining a high-band signal of the current frame based on the high-band parameter; and obtaining a synthesis signal of the current frame based on the low-band signal and the high-band signal.
Abstract:
An audio signal classification method includes determining, according to voice activity of a current audio frame, whether to obtain a frequency spectrum fluctuation of the current audio frame and store the frequency spectrum fluctuation in a frequency spectrum fluctuation memory, and updating, according to whether the audio frame is percussive music or activity of a historical audio frame, frequency spectrum fluctuations stored in the frequency spectrum fluctuation memory, and classifying the current audio frame as a speech frame or a music frame according to statistics of a part or all of effective data of the frequency spectrum fluctuations stored in the frequency spectrum fluctuation memory.
Abstract:
An image processing method to reduce access pressure of each image in an image set, where the image processing method includes obtaining a quantity of times each image layer in an image set is accessed, determining one or more first image layers, where a quantity of times the first image layer in the image set is accessed is greater than a first threshold, and the first image layer has at least two child image layers, generating a copy of the first image layer, and modifying some child image layers of the first image layer to child image layers of the copy of the first image layer.