A digital-to-analog conversion device which performs integration processing for integrating a difference between an input signal and a first return signal generated based on the input signal, and outputting an integration result, first quantization processing for quantizing the integration result, and outputting a first quantization signal, first return signal output processing for outputting the first return signal by adding to the first quantization signal a correction value delay signal acquired by a correction value signal outputted based on the integration result being delayed, and output processing for outputting output signals including a signal whose pulse width is asymmetrical to center of a processing period, based on the first quantization signal, in which the correction value signal includes a signal indicating a correction value for correcting a difference between a center of the pulse width asymmetrical to the center of the processing period and the center of the processing period.

A digital-to-analog conversion device which performs integration processing for integrating a difference between an input signal and a first return signal generated based on the input signal, and outputting an integration result, first quantization processing for quantizing the integration result, and outputting a first quantization signal, first return signal output processing for outputting the first return signal by adding to the first quantization signal a correction value delay signal acquired by a correction value signal outputted based on the integration result being delayed, and output processing for outputting output signals including a signal whose pulse width is asymmetrical to center of a processing period, based on the first quantization signal, in which the correction value signal includes a signal indicating a correction value for correcting a difference between a center of the pulse width asymmetrical to the center of the processing period and the center of the processing period.

A computer-implemented sound signal synthesis method generates control data including pitch notation data indicative of a pitch name of a pitch of a sound signal to be synthesized and octave data indicative of an octave of the pitch of the sound signal to be synthesized; and estimates output data indicative of the sound signal to be synthesized by inputting the generated control data into a generative model that has learned a relationship between training control data including training pitch notation data indicative of a pitch name of a pitch of a reference signal and training octave data indicative of an octave of the pitch of the reference signal; and training output data indicative of the reference signal.

A computer-implemented sound signal synthesis method generates control data including pitch notation data indicative of a pitch name of a pitch of a sound signal to be synthesized and octave data indicative of an octave of the pitch of the sound signal to be synthesized; and estimates output data indicative of the sound signal to be synthesized by inputting the generated control data into a generative model that has learned a relationship between training control data including training pitch notation data indicative of a pitch name of a pitch of a reference signal and training octave data indicative of an octave of the pitch of the reference signal; and training output data indicative of the reference signal.

According to an embodiment, there is provided a system and method for automatic AI controlled loop based song construction. It provides and benefits from a machine learning AI in a audio loop selection engine for the generation of a song structure and for the selection of fitting audio loops from a database of audio loops. In one embodiment, the instant method provides a music generation process that utilizes an AI system that has been trained and validated on a music item database to complete the creation of a music item given an incomplete song that was started but not finished by a user.

According to an embodiment, there is provided a system and method for automatic AI controlled loop based song construction. It provides and benefits from a machine learning AI in a audio loop selection engine for the generation of a song structure and for the selection of fitting audio loops from a database of audio loops. In one embodiment, the instant method provides a music generation process that utilizes an AI system that has been trained and validated on a music item database to complete the creation of a music item given an incomplete song that was started but not finished by a user.

The described technology is generally directed towards providing a visible waveform representation of an audio signal, by processing the audio signal with a polynomial (e.g., cubic) mapping function. Coefficients of the polynomial mapping function are predetermined based on constraints (e.g., slope information and desired range of the resultant curve), and whether the plotted audio waveform corresponds to sound field quantities or power quantities. Once the visible representation of the reshaped audio waveform is displayed, audio and/or video editing operations can be performed, e.g., by time-aligning other audio or video with the reshaped audio waveform, and/or modifying the reshaped audio waveform to change the underlying audio data.

The described technology is generally directed towards providing a visible waveform representation of an audio signal, by processing the audio signal with a polynomial (e.g., cubic) mapping function. Coefficients of the polynomial mapping function are predetermined based on constraints (e.g., slope information and desired range of the resultant curve), and whether the plotted audio waveform corresponds to sound field quantities or power quantities. Once the visible representation of the reshaped audio waveform is displayed, audio and/or video editing operations can be performed, e.g., by time-aligning other audio or video with the reshaped audio waveform, and/or modifying the reshaped audio waveform to change the underlying audio data.

A computer-implemented sound signal generation method includes: obtaining a first sound source spectrum of a sound signal to be generated; obtaining a first spectral envelope of the sound signal; and estimating fragment data representative of samples of the sound signal based on the obtained first sound source spectrum and the obtained first spectral envelope.

A computer-implemented sound signal generation method includes: obtaining a first sound source spectrum of a sound signal to be generated; obtaining a first spectral envelope of the sound signal; and estimating fragment data representative of samples of the sound signal based on the obtained first sound source spectrum and the obtained first spectral envelope.