33 results about "Audio watermark" patented technology

A method includes adding, by a first computing device, a first audio watermark to first speech data corresponding to playback of a first utterance including a hotword used to invoke an attention of a second computing device. The method includes outputting, by the first computing device, the playback of the first utterance corresponding to the watermarked first speech data. The second computing device is configured to receive the watermarked first speech data and determine to cease processing of the watermarked first speech data.

Methods, systems, and user devices for suppressing hotword triggering when a hotword in a recorded media is detected are disclosed, including computer programs encoded on computer storage media. In an aspect, a method includes receiving, at data processing hardware, audio data corresponding to playback of a media content item, the audio data including an audio watermark and an utterance of a command preceded by a hotword; determining, by the data processing hardware, that the received audio data includes the hotword; processing, by the data processing hardware, the audio data to: identify the audio watermark included in the audio data; and determine a corresponding bitstream of the audio watermark; and based on the determined corresponding bitstream of the audio watermark, determining, by the data processing hardware, to bypass performing the command preceded by the hotword without accessing an audio watermark database to identify a matching audio watermark.

The invention provides an audio watermark embedding method and device and a conference system, and relates to the technical field of digital watermarking. And obtaining an original audio collected from an environment where the terminal is located in the first time period, wherein the original audio comprises an audio played by the terminal in the first time period. The playing audio is configured to be embedded with a watermark based on the first watermark embedding parameter value by using a first watermark embedding algorithm. And carrying out watermark extraction on the original audio according to the first watermark embedding algorithm. And if the watermark extraction from the original audio fails, embedding the watermark in the audio to be played of the terminal based on the second watermark embedding parameter value by using the first watermark embedding algorithm to obtain a new played audio. Under the condition that the watermark cannot be successfully extracted from the original audio, the watermark embedding parameter value is adjusted, so that the watermark embedded in the audio played later by the terminal can adapt to the environment and is successfully extracted, the adaptive environment adjustment of the audio watermark is realized, and the robustness of the audio watermark is improved.

Described is a neural network based system for use in audio watermarking, comprising: a neural network based watermark generator configured for embedding, based on a learnable embedding table, a predefined watermark into an input audio signal, thereby obtaining a watermarked audio signal; and a neural network based watermark detector comprising: a detection head that is configured for determining presence or absence of a watermark in a target audio signal; and a decoding head that is configured for decoding the watermark from the target audio signal, wherein the embedding table is shared between the watermark generator and the watermark detector, such that the decoding of the watermark from the target audio signal is based on the embedding table that has been used for the embedding.

The invention discloses an audio watermark generation and detection method. The method comprises the following steps: acquiring an audio signal corresponding to an audio to be processed; the amplitude of the confrontation disturbance signal is smaller than that of a value set corresponding to a psychological acoustic masking threshold value of the audio signal, the psychological acoustic masking threshold value is used for quantitatively representing an added disturbance amplitude upper limit corresponding to each frequency point in the audio signal, and the confrontation disturbance signal is used for carrying watermark information of the audio to be processed; and embedding the adversarial disturbance signal into the audio signal. The technical problem that the audio watermarking technology adopted in the related technology is mostly based on a static or dominant embedding mode and is easily removed by an attacker through a signal processing method is solved.

The invention discloses a robust audio watermarking method based on an adaptive quantization strategy and feature classification, and belongs to the technical field of digital audio copyright protection. The method comprises the following steps: framing an audio signal, extracting a logarithmic mean feature (DWT-CLM) of discrete wavelet transform, and combining a zero-crossing rate, a variance and energy to form a frame feature vector; a Sigmoid classifier is used to discriminate frame characteristics, and a fixed or variable quantization step size is adaptively selected to embed watermark bits into approximate components; and during extraction, the watermark is accurately extracted through the same feature analysis and classifier discrimination recovery quantization mode. Experiments show that the algorithm has better inaudible property and robustness, can effectively resist attacks such as MP3 compression, resampling, low-pass filtering and re-recording, and is suitable for digital audio copyright protection scenes.

The invention relates to an audio watermark embedding and extracting method for resisting a desynchronization attack, which comprises the following steps of: bearing an embedded bit by using three sections of intermediate-frequency average energy at an embedded end, implementing a triangular modulation strategy on the three sections of average energy according to the embedded bit, and introducing buffer compensation at the embedded end; uniformly scaling all frequency domain coefficients according to a proportion for the buffer expansion interval by taking a segment as a unit, carrying out inverse transformation on the whole frame to obtain frames containing watermarks, and splicing the frames containing the watermarks into audio containing the watermarks; judgment is only carried out on a target frequency band at an extraction side, clipping detection is carried out through symmetric consistency discrimination, rapid and reliable resynchronization in a clipping scene is realized in combination with double-end sliding window search, and blind detection is realized on the premise of not depending on original audio. Compared with the prior art, the method has the advantages that the balance among the watermark capacity, the robustness and the hearing feeling during desynchronization attack resistance is realized, the robustness is improved, and the like.

Embodiments of the present application disclose an audio watermark adding method, comprising: a playing terminal acquiring a first audio in real time; the playing terminal embedding an audio watermark in the first audio, the audio watermark being associated with the playing terminal; and the playing terminal playing the first audio with the embedded audio watermark. Embodiments of the present application also provide an audio watermark analysis method and device and a medium, in a scenario of playing an audio in real time, a playing terminal adds an audio watermark in an audio stream in real time, so that a later device can determine the playing terminal according to the audio watermark when analyzing the watermark, and tracing is facilitated after the first audio is transcribed.

The application discloses a method and device for training a reversible neural network for audio watermark processing. The method comprises: obtaining a sample data set; repeatedly performing the following process until the target loss value is less than the preset threshold, stopping iteration, and obtaining a target reversible neural network: adding watermark information to each sample audio data in the target training set according to the encoder of the initial reversible neural network to obtain a plurality of first sample audio data embedded with watermark information; performing simulated attacks on the plurality of first sample audio data according to a weighted attack strategy to obtain a plurality of second sample audio data; decoding the plurality of second sample audio data according to the decoder of the initial reversible neural network to obtain restored watermark information of each second sample audio data; determining the target loss value according to the loss value corresponding to all sample audio data, and adjusting the network parameters of the initial reversible neural network according to the target loss value.

Disclosed example people monitoring methods include detecting a first watermark in a first audio signal obtained from an acoustic sensor, the first watermark identifying media presented by a monitored media device, determining whether a second watermark, different from the first watermark, is embedded in the first audio signal obtained from the acoustic sensor, the second watermark identifying at least one of a mobile device or a user of the mobile device, classifying the second watermark as a media watermark or a people monitoring watermark based on a characteristic of the second watermark, and when the second watermark is determined to be embedded in the first audio signal, reporting at least one of the second watermark or information decoded from the second watermark to identify at least one of the mobile device or the user of the mobile device as being exposed to the media presented by the monitored media device.

The application provides a multi-bit audio watermarking method based on phase distribution and high-efficiency bit mapping, and belongs to the field of audio information hiding. The application divides multiple independent phase subintervals based on the natural distribution characteristics of phases, and can realize one-to-many mapping from single feature to multi-bit watermarking by constructing unique phase features in the phase subintervals corresponding to watermarking information. In addition, the application introduces an optimization strategy, and can realize automatic phase redistribution. The application can significantly reduce the number of subspaces / feature modes required for multi-bit embedding, and reduce the design difficulty of the multi-bit watermarking algorithm. In addition, since an automatic phase redistribution algorithm based on optimization constraints is adopted, the algorithm can more effectively balance the inaudibility and robustness.

The invention provides an audio watermark embedding method and device, electronic equipment and a storage medium, and belongs to the technical field of audio processing, and the method comprises the steps: obtaining the amplitude spectrum characteristics of an original audio signal, and determining a watermark embedding energy mask; inputting the amplitude spectrum features into a plurality of mask prediction network models to obtain watermark embedding risk masks; determining a target watermark embedding risk mask according to the watermark embedding risk mask to generate a frame-level embedding mask; and embedding the watermark information into the feature component corresponding to the target audio frame to obtain a watermark-containing amplitude spectrum feature, and performing inverse time-frequency transformation on the watermark-containing amplitude spectrum feature to obtain a watermark-containing audio signal. According to the method, the audio energy and the model prediction risk are combined, the audio frame which is most suitable for embedding the watermark is adaptively screened out, modification in hearing sensitive frames such as silent frames and transient frames is avoided, the problem that the audio quality is reduced due to undifferentiated embedding of the watermark is solved, and on the premise that the watermark robustness is not sacrificed, the watermark embedding efficiency is improved. And the imperceptibility of the watermark and the auditory quality of the audio containing the watermark are obviously improved.

The invention discloses a high-robustness lossless high-capacity audio watermark embedding method based on deep learning, and relates to the technical field of digital watermarking. The method comprises the following steps of audio-watermark information preprocessing, watermark information embedding and watermark embedding detection and judgment. According to the method, the original audio and the watermark information to be embedded are correspondingly preprocessed, so that the quality of the original audio and the watermark information is effectively improved, the subsequent embedding process is more efficient and accurate, then the preprocessed audio and watermark information are input into the audio embedding network to output the watermark audio, and the watermark embedding efficiency is improved. According to the method, high-capacity watermark information is embedded, audio distortion in the embedding process is effectively avoided, the quality of the embedded audio is guaranteed, finally, the stability and the anti-jamming capability of the embedded watermark can be effectively detected by introducing adversarial training attack simulation, the audio distortion is reduced to the maximum extent while the watermark capacity is guaranteed, and the watermark quality is improved. And the anti-interference capability of the watermark is improved.

A method includes adding, by a first computing device, a first audio watermark to first speech data corresponding to playback of a first utterance including a hotword used to invoke an attention of a second computing device. The method includes outputting, by the first computing device, the playback of the first utterance corresponding to the watermarked first speech data. The second computing device is configured to receive the watermarked first speech data and determine to cease processing of the watermarked first speech data.

An audio watermark embedding method (600) and apparatus, and a conference system, relating to the technical field of digital watermarking. The method (600) comprises: acquiring first original audio collected, during a first time period, from an environment where a first terminal is located, the first original audio comprising first playback audio played back by the first terminal during the first time period, and the first playback audio being configured to use a first watermark embedding algorithm to embed a first watermark on the basis of a first watermark embedding parameter value (601); performing watermark extraction on the first original audio on the basis of the first watermark embedding algorithm (602); and if the extraction of the first watermark from the first original audio fails, using the first watermark embedding algorithm to embed, on the basis of a second watermark embedding parameter value, the first watermark into first audio to be played back that is to be played back by the first terminal, so as to obtain second playback audio, the second watermark embedding parameter value differing from the first watermark embedding parameter value, and the second playback audio being configured to be played back by the first terminal during a second time period (603).

Techniques are described for hybrid masking threshold-based perceptual slacks for audio watermarking. In some embodiments, the techniques include identifying an audio signal, determining perceptual slacks for the audio signal, generating a watermarked audio signal that includes an audio watermark based on the perceptual slacks, and outputting the watermarked audio signal using one or more speakers, for localization of the one or more speakers.

The invention provides a deep robust audio watermarking method based on diffusion model residual block modulation. The method comprises the following steps: firstly, constructing a conditional modulation signal through fusion of a watermark vector and time step embedding; the method is characterized in that a feature-level linear modulation module FiLM is integrated in a residual block of a diffusion noise prediction network, and deep penetration of watermark information in a multi-level feature space is realized through channel-level scaling and offset; in the embedding stage, a deterministic scheduler is utilized to perform forward noise addition on audio, and intensity weighting and superposition are performed on predicted noise obtained by single reasoning in combination with a self-adaptive masking graph generated by local energy distribution. According to the method, the problems of shallow watermark embedding and weak feature coupling are solved, and the robustness under the interference of filtering, compression and the like is remarkably improved.

A system for avoiding double processing using audio watermarking. A decoder inserts an audio watermark during a transient in an audio signal. This avoids the drawbacks of using out-of-band control signals or metadata. The decoder performs: detecting a transient in a first audio signal; transforming a portion related to the transient into a frequency domain to compare a first frequency band of the frequency domain data to a second frequency band of the frequency domain data; when the first frequency band is not related to the second frequency band, the decoder performs processing on the first audio data to generate second audio data; when the first frequency band is related to the second frequency band, the first audio data is used as the second audio data without performing any processing.

A method and system for adding overtly human-perceptible supplemental audio content into a media stream to help mask audio effects of an audio watermark in the media stream. A method involves receiving a media stream that defines a sequence of audio content presentable by a content presentation device, modifying the media stream to produce a modified media stream that defines the sequence of audio content, and outputting the modified media stream for presentation by the content presentation device. The modified media stream includes an audio watermark that is machine-detectable to trigger an interactive event. Further, the act of modifying the media stream involves adding into the media stream supplemental audio content coincident with the audio watermark, to help mask the audio watermark in the modified media stream during presentation of the modified media stream by the content presentation device.

The application provides a method and device for generating and detecting audio watermark, electronic equipment, storage medium and computer program product. The method comprises: extracting second audio data from first audio data, wherein the loudness of the sound included in the second audio data is greater than a loudness threshold; encoding the second audio data to obtain an audio feature of the second audio data; encoding preset watermark information to obtain a watermark feature; first fusing the watermark feature and the audio feature to obtain a first fused feature; and decoding based on the first fused feature to obtain third audio data in which the watermark information is embedded. Through the application, the efficiency of embedding watermark information can be improved while ensuring the quality of the original audio data.

Disclosed example people monitoring methods include detecting a first watermark in a first audio signal obtained from an acoustic sensor, the first watermark identifying media presented by a monitored media device, determining whether a second watermark, different from the first watermark, is embedded in the first audio signal obtained from the acoustic sensor, the second watermark identifying at least one of a mobile device or a user of the mobile device, classifying the second watermark as a media watermark or a people monitoring watermark based on a characteristic of the second watermark, and when the second watermark is determined to be embedded in the first audio signal, reporting at least one of the second watermark or information decoded from the second watermark to identify at least one of the mobile device or the user of the mobile device as being exposed to the media presented by the monitored media device.

The application relates to the field of artificial intelligence and audio processing technology, can be applied to the fields of intelligent medical treatment and financial technology, and discloses an audio watermark processing method, device, equipment and medium, which comprises the following steps: encoding audio blocks continuously input, obtaining an audio feature vector; acquiring a digital watermark, using a multilayer perceptron to time-modulate the digital watermark according to the audio length of the blocks, obtaining a watermark hidden vector; embedding the watermark hidden vector into the audio feature vector, obtaining a target audio vector; quantizing the target audio vector, generating a target audio spectrum embedded with the digital watermark; and decoding the target audio spectrum to obtain a target audio. The application encodes audio blocks continuously input, can adapt to a streaming scenario, processes audio data in sections, meets the watermark embedding requirement of continuous audio streaming, can compress audio, effectively reduces the data volume, reduces the transmission time consumption, and meets the low-delay communication requirement.

The application provides an audio watermark embedding method and device, electronic equipment and storage medium, and belongs to the technical field of audio processing. The method comprises the following steps: obtaining the amplitude spectrum feature of an original audio signal and determining a watermark embedding energy mask; inputting the amplitude spectrum feature into a plurality of mask prediction network models to obtain a watermark embedding risk mask; determining a target watermark embedding risk mask according to the watermark embedding risk mask to generate a frame-level embedding mask; embedding watermark information into the feature component corresponding to the target audio frame to obtain a watermark-containing amplitude spectrum feature, and performing inverse time-frequency conversion on the watermark-containing amplitude spectrum feature to obtain a watermark-containing audio signal. The application combines audio energy and model prediction risk to adaptively select the most suitable audio frame for embedding a watermark, avoids modification in silent, transient and other auditory sensitive frames, solves the problem of audio quality degradation caused by indiscriminate watermark embedding, and significantly improves the imperceptibility of the watermark and the auditory quality of the watermark-containing audio without sacrificing the robustness of the watermark.

The invention provides an audio playing method, device and equipment, and relates to the technical field of computers. An original audio generated in a local environment is collected by a device, watermark embedding processing is carried out based on the original audio to obtain a target audio embedded with an audio watermark, and then the target audio is played. Through real-time acquisition, real-time watermark embedding and real-time playing of the audio generated in the local environment, audio watermark embedding for an offline scene is realized, and audio tracing of the offline scene is realized.

Disclosed in the present invention are an audio watermark embedding and extraction method and system. The method comprises: acquiring audio data, calculating a masking threshold for each frequency point of the audio data, and preprocessing the audio data; performing encoding on the basis of watermark information to generate an audio watermark, and embedding the audio watermark into the audio data on the basis of the masking threshold of the audio data; and locating the position of the audio watermark in the audio data into which the audio watermark is embedded, and extracting the audio watermark on the basis of the masking threshold of the original audio data. In the present invention, an audio watermark is embedded on the basis of human auditory masking theory; the masking threshold of audio data is calculated, and the audio watermark is added to audio in a frequency domain on the basis of the masking threshold, thereby allowing the audio watermark to better resist these attacks, ensuring the robustness of the audio watermark, and ensuring that the detectability can be maintained even under harsh conditions. The present invention solves the problem whereby existing audio watermarks have insufficient robustness and are prone to affect the quality of audio itself.

This invention provides a model training, audio watermark embedding, and extraction method, device, and medium. The model training method includes: acquiring a first audio sample and a second audio sample obtained by embedding a first watermark information into the first audio sample; determining the watermark embedding cost weight of each segment based on the speech intelligibility between each segment in the first audio sample and the corresponding segment in the second audio sample; determining the watermark embedding loss based on the watermark embedding cost weight of each segment and the acoustic feature difference between each segment and the corresponding segment in the second audio sample; and training the model based on the watermark embedding loss to obtain an audio watermark model. The method, device, and medium provided by this invention can assess the risk of sound quality degradation caused by watermark information embedding in different segments based on the differences in human auditory characteristics. Therefore, during the training process, it can focus on optimizing the acoustic feature difference of segments with higher watermark embedding cost weights, thereby optimizing the user's subjective auditory experience.

An audio processing method and apparatus, a computer device, and a storage medium are provided. The method includes: segmenting an input audio to obtain a plurality of audio segments, and determining an original frequency domain coefficient for each of the plurality of audio segments; obtaining reference information including positioning information and watermark information; determining, for each of the plurality of audio segments and based on the reference information, adjustment information for adjusting the original frequency domain coefficient of the respective audio segment; performing inverse frequency domain transformation on the adjustment information, to obtain a reference segment corresponding to the respective audio segment; and combining, for each of the plurality of audio segments, the respective audio segment and the corresponding reference segment, to obtain a target audio segment, thereby obtaining a plurality of target audio segments; and obtaining, based on the plurality of target audio segments, a target audio.

The application discloses a frequency dynamic convolution-based anti-compression-encoding robust audio watermarking method and system, relates to the field of multimedia information security, and comprises the following steps: an audio frequency domain conversion step, a watermark encoding step, a watermark embedding step, an audio waveform reconstruction step and a watermark extraction step. The application improves the robustness of the watermark to various signal processing while ensuring the imperceptibility of the watermark, effectively solves the watermark failure problem caused by compression encoding in the traditional watermarking method, can better learn to embed the watermark in the robust and imperceptible area in the frequency domain, and enhances the copyright protection and traceability of the watermark in the real application scene with multiple compressions.