A method of decoding an audio or speech signal, the method including the steps of: (a) receiving, by a receiver, a coded bitstream including the audio or speech signal and conditioning information; (b) providing, by a bitstream decoder, decoded conditioning information in a format associated with a first bitrate; (c) converting, by a converter, the decoded conditioning information from the format associated with the first bitrate to a format associated with a second bitrate, the first bitrate being lower than the second bitrate; and (d) providing, by a generative neural network, a reconstruction of the audio or speech signal according to a probabilistic model conditioned by the decoded conditioning information in the format associated with the second bitrate, wherein the generative neural network reconstructs the signal by performing sampling from a conditional probability density function, which is conditioned using the conditioning information in the format associated with the second bitrate, and wherein the generative neural network is a SampleRNN neural network; wherein the conditioning information includes an embedded part and a non-embedded part; wherein the conditioning information includes one or more conditioning parameters; and wherein a dimensionality, which is defined as a number of the conditioning parameters, of the embedded part of the conditioning information associated with the first bitrate is lower than or equal to the dimensionality of the embedded part of the conditioning information associated with the second bitrate, and wherein the dimensionality of the non-embedded part of the conditioning information associated with the first bitrate is the same as the dimensionality of the non-embedded part of the conditioning information associated with the second bitrate. (a) receiving, by a receiver, a coded bitstream including the audio or speech signal and conditioning information; (b) providing, by a bitstream decoder, decoded conditioning information in a format associated with a first bitrate; (c) converting, by a converter, the decoded conditioning information from the format associated with the first bitrate to a format associated with a second bitrate, the first bitrate being lower than the second bitrate; and (d) providing, by a generative neural network, a reconstruction of the audio or speech signal according to a probabilistic model conditioned by the decoded conditioning information in the format associated with the second bitrate, wherein the generative neural network reconstructs the signal by performing sampling from a conditional probability density function, which is conditioned using the conditioning information in the format associated with the second bitrate, and wherein the generative neural network is a SampleRNN neural network; wherein the conditioning information includes an embedded part and a non-embedded part; wherein the conditioning information includes one or more conditioning parameters; and wherein a dimensionality, which is defined as a number of the conditioning parameters, of the embedded part of the conditioning information associated with the first bitrate is lower than or equal to the dimensionality of the embedded part of the conditioning information associated with the second bitrate, and wherein the dimensionality of the non-embedded part of the conditioning information associated with the first bitrate is the same as the dimensionality of the non-embedded part of the conditioning information associated with the second bitrate. <EOS>