4 results about "Speaker recognition system" patented technology

The invention discloses a speaker recognition model frequency modulation trigger injection method, particularly relates to the technical field of voice signal processing and artificial intelligence safety, and is used for solving the problems that an existing speaker recognition model back door injection method is insufficient in concealment, poor in black box environment adaptability, prone to distortion of trigger characteristics in the physical transmission process and poor in safety. And mainstream defense strategies such as model fine tuning, pruning and spectrum detection are difficult to resist. The method comprises the following steps: constructing a piecewise linear periodic low-frequency modulation curve for original voice, generating a smooth phase track according to a frequency and phase relationship, constructing a sinusoidal modulator to generate a hidden sample, mixing normal samples in proportion and uniformly marking, training a model by a black box, testing reproduction modulation and inputting the model; according to the method, the defects of insufficient concealment, black box adaptability, physical robustness and defensive resistance of an existing method are overcome, high-concealment, high-robustness and wide-application backdoor injection is realized, and reliable support is provided for security evaluation of a speaker recognition system.

The present application relates to the technical field of voiceprint recognition, and particularly relates to a text-independent speaker verification method based on identity information and semantic information disentanglement. The technical scheme of the present application is completed by building a neural network, training a model, and testing a result. sch The semantic content is represented by a fixed-length feature f spk The correlation between the voiceprint feature f sch and the semantic feature f sch is calculated using a disentanglement method such as mutual information to achieve disentanglement between the voiceprint feature and the semantic feature, obtain more accurate and robust speaker voiceprint features, and solve the problem of poor system generalization performance caused by interference of semantic content factors in the data set extracted by the speaker recognition system.

This invention relates to the field of speech adversarial example defense, specifically a novel feature fusion defense training method based on speaker facial features, comprising: (1) constructing an audio-video dataset; (2) concatenating audio-video vectors to build a feature fusion module with a multi-head attention mechanism; (3) training the speaker recognition system by retaining only the audio feature portion of the cross-modal fusion features; and (4) generating adversarial examples using FGSM, PGD, CW, FakeBob, SirenAttack, and Kenansville for defense performance testing. This invention introduces speaker facial feature identity consistency information during speaker identity registration to train the speaker recognition system. In the case of unknown attack methods, cross-modal information enhances the robustness and accuracy of the speaker recognition system, achieving defense against adversarial examples of unknown attack methods.