A method for packet loss concealment of an incomplete audio signal, the incomplete audio signal comprising a substitute signal portion replacing an original signal portion of a complete audio signal, the method comprising: obtaining a representation of the incomplete audio signal; inputting the representation of the incomplete audio signal to an encoder neural network trained to predict a latent representation of a complete audio signal given a representation of an incomplete audio signal; outputting, by the encoder neural network, a latent representation of a predicted complete audio signal; quantizing the latent representation of the complete audio signal to obtain a quantized latent representation, wherein the quantized latent representation is formed by selecting a set of tokens out of a predetermined vocabulary set of tokens; conditioning, with at least one token of the quantized latent representation, a generative neural network, wherein the generative neural network is trained to predict a token of the set of tokens provided at least one different token of the set of tokens; outputting by the generative neural network a predicted token of the latent representation and a confidence metric associated with the predicted token; based on the confidence metric of the predicted token, replacing a corresponding token of the quantized latent representation with the predicted token, inputting the quantized latent representation of the predicted complete audio signal to a decoder neural network trained to predict a representation of a complete audio signal given a latent representation of a complete audio signal; and outputting, by the decoder neural network, a representation of the predicted complete audio signal comprising a reconstruction of the original portion of the complete audio signal, wherein said encoder neural network and said decoder neural network have been trained with an adversarial neural network. obtaining a representation of the incomplete audio signal; inputting the representation of the incomplete audio signal to an encoder neural network trained to predict a latent representation of a complete audio signal given a representation of an incomplete audio signal; outputting, by the encoder neural network, a latent representation of a predicted complete audio signal; quantizing the latent representation of the complete audio signal to obtain a quantized latent representation, wherein the quantized latent representation is formed by selecting a set of tokens out of a predetermined vocabulary set of tokens; conditioning, with at least one token of the quantized latent representation, a generative neural network, wherein the generative neural network is trained to predict a token of the set of tokens provided at least one different token of the set of tokens; outputting by the generative neural network a predicted token of the latent representation and a confidence metric associated with the predicted token; based on the confidence metric of the predicted token, replacing a corresponding token of the quantized latent representation with the predicted token, inputting the quantized latent representation of the predicted complete audio signal to a decoder neural network trained to predict a representation of a complete audio signal given a latent representation of a complete audio signal; and outputting, by the decoder neural network, a representation of the predicted complete audio signal comprising a reconstruction of the original portion of the complete audio signal, wherein said encoder neural network and said decoder neural network have been trained with an adversarial neural network.