Abstract: A method and device of transparency processing of music. The method comprises: obtaining a characteristic of a music to be played; inputting the characteristic into a transparency probability neural network to obtain a transparency probability of the music to be played; determining a transparency enhancement parameter corresponding to the transparency probability, the transparency enhancement parameter is used to perform transparency adjustment on the music to be played. The present invention constructs a transparency probability neural network in advance based on deep learning and builds a mapping relationship between the transparency probability and the transparency enhancement parameters can be constructed, so that the music to be played can be automatically permeated.

Abstract: A deep learning method-based tonal balancing method, apparatus, and system, the method includes: extracting features from audio data to obtain audio data features, generating audio balancing results by using a trained audio balancing model based on the obtained audio data features. The present invention employs deep neural networks and unsupervised deep learning method to solve the problems of audio balancing of unlabeled music and music of unknown style. The present invention also combines user preferences statistics to achieve a more rational multi-style audio balancing design to meet individual needs.

Abstract: The present invention provides a deep learning based method and system for processing sound quality characteristics. The method comprises: obtaining data characteristics of an audio data to be processed by extracting features from user preference data including the audio data to be processed; based on the data characteristics, generating a sound quality processing result of the audio to be processed by using a trained baseline model; wherein the baseline model is a neural network model trained by using audio data behavioral data, and other relevant data from multiple users or a single user.

Abstract: The present invention provides a deep learning based method and system for processing sound quality characteristics. The method comprises: obtaining data characteristics of an audio data to be processed by extracting features from user preference data including the audio data to be processed; based on the data characteristics, generating a sound quality processing result of the audio to be processed by using a trained baseline model; wherein the baseline model is a neural network model trained by using audio data behavioral data, and other relevant data from multiple users or a single user.

Abstract: The present invention provides a deep learning based method and system for processing sound quality characteristics. The method comprises: obtaining data characteristics of an audio data to be processed by extracting features from user preference data including the audio data to be processed; based on the data characteristics, generating a sound quality processing result of the audio to be processed by using a trained baseline model; wherein the baseline model is a neural network model trained by using audio data behavioral data, and other relevant data from multiple users or a single user.

Abstract: The present disclosure is drawn to printable media. A printable medium includes a substrate having a first side and a second side. An ink-receiving layer is positioned on the first side of the substrate. The ink-receiving layer includes a colloidal sol. An ink-penetrable layer is positioned on the ink-receiving layer. The ink-penetrable layer includes a binder and polymer particles having a glass transition temperature from 80° C. to 150° C. A repositionable adhesive layer is positioned on the second side of the substrate. A release liner is removably positioned on the repositionable adhesive layer. A friction control layer is positioned on the release liner, where the friction control layer includes a slip aid.

Abstract: The present invention provides a deep learning based method and system for processing sound quality characteristics. The method comprises: obtaining data characteristics of an audio data to be processed by extracting features from user preference data including the audio data to be processed; based on the data characteristics, generating a sound quality processing result of the audio to be processed by using a trained baseline model; wherein the baseline model is a neural network model trained by using audio data behavioral data, and other relevant data from multiple users or a single user.

Abstract: The present disclosure is drawn to printable media. A printable medium includes a substrate having a first side and a second side. An ink-receiving layer is positioned on the first side of the substrate. The ink-receiving layer includes a colloidal sol. An ink-penetrable layer is positioned on the ink-receiving layer. The ink-penetrable layer includes a binder and polymer particles having a glass transition temperature from 80° C. to 150° C. A repositionable adhesive layer is positioned on the second side of the substrate. A release liner is removably positioned on the repositionable adhesive layer. A friction control layer is positioned on the release liner, where the friction control layer includes a slip aid.

Abstract: A deep learning method-based tonal balancing method, apparatus, and system, the method includes: extracting features from audio data to obtain audio data features, generating audio balancing results by using a trained audio balancing model based on the obtained audio data features. The present invention employs deep neural networks and unsupervised deep learning method to solve the problems of audio balancing of unlabeled music and music of unknown style. The present invention also combines user preferences statistics to achieve a more rational multi-style audio balancing design to meet individual needs.

Abstract: A method and device of transparency processing of music. The method comprises: obtaining a characteristic of a music to be played; inputting the characteristic into a transparency probability neural network to obtain a transparency probability of the music to be played; determining a transparency enhancement parameter corresponding to the transparency probability, the transparency enhancement parameter is used to perform transparency adjustment on the music to be played. The present invention constructs a transparency probability neural network in advance based on deep learning and builds a mapping relationship between the transparency probability and the transparency enhancement parameters can be constructed, so that the music to be played can be automatically permeated.

Abstract: Disclosed herein is a printable recording media comprising a cellulose based substrate and a composite ink receiving layer that includes a first distinct layer and a second distinct layer. The second distinct layer is applied on top of the first distinct layer and comprises, at least, a polymeric binder, nano-size inorganic pigment particles and an ionene compound. Also disclosed herein is a method for making the printable recording media.

Abstract: The present disclosure is drawn to hybrid media sheets, ink-receiving layer compositions for coating on a media substrate, and a method of making hybrid media sheets. The hybrid media sheet scan have a media substrate with a front barrier layer, a back barrier layer, an adhesion promoting layer applied to the front barrier layer, and an ink-receiving layer applied to the adhesion promoting layer. The ink-receiving layer can include a water-soluble polymer, a mordant, and particles of a metal- or semimetal-oxide.

Abstract: Disclosed herein is a printable recording media comprising a cellulose based substrate and a composite ink receiving layer that includes a first distinct layer and a second distinct layer. The second distinct layer is applied on top of the first distinct layer and comprises, at least, a polymeric binder, nano-size inorganic pigment particles and a thermoplastic material. Also disclosed herein is a method for making the printable recording media.

Abstract: Disclosed herein is a printable recording media comprising a cellulose based substrate and a composite ink receiving layer that includes a first distinct layer and a second distinct layer. The second distinct layer is applied on top of the first distinct layer and comprises, at least, a polymeric binder, nano-size inorganic pigment particles and an ionene compound. Also disclosed herein is a method for making the printable recording media.

Abstract: An inkjet printer can include an inkjet printhead to print an image on a print medium, and a dryer to reduce or remove moisture from the image. A post-printing treatment fluid can also be present which can include water and a flatness control agent, the flatness control agent including an organic solvent with three or more hydroxyl groups, and a vapor pressure less than 2×10?4 mmHg. A fluid dispenser can be included to apply the post-printing treatment fluid on the print medium after the moisture from the image is reduced or removed. Additionally, the printer can include a mechanical calendering device to apply pressure to the print medium after application and while the print medium is still moistened by the post-printing treatment fluid.

Abstract: The present disclosure is drawn to coated print media, a method of preparing print media, and a printing system. The coated print media can comprise a substrate and a coating applied to the substrate. The coating can include, by dry weight, 5 wt % to 60 wt % of a polymeric binder having a Tg below 50 C, 10 wt % to 60 wt % of cationic latex having a Tg from 50 C to 130 C, 5 wt % to 30 wt % of a multivalent cationic salt, and 2 wt % to 25 wt % of a high density polyethylene wax.

Abstract: Disclosed herein is a printable recording media including a substrate and, at least, an ink receiving layer that includes a first distinct layer and a second distinct layer that is applied on top of the first distinct layer. The first distinct layer includes an electrical charged substance and the second distinct layer includes, at least, a polymeric binder and nano-size inorganic pigment particles. Also disclosed herein is a method for making the printable recording media.

Abstract: An inkjet printer can include an inkjet printhead to print an image on a print medium, and a dryer to reduce or remove moisture from the image. A post-printing treatment fluid can also be present which can include water and a flatness control agent, the flatness control agent including an organic solvent with three or more hydroxyl groups, and a vapor pressure less than 2×10?4 mmHg. A fluid dispenser can be included to apply the post-printing treatment fluid on the print medium after the moisture from the image is reduced or removed. Additionally, the printer can include a mechanical calendering device to apply pressure to the print medium after application and while the print medium is still moistened by the post-printing treatment fluid.

Abstract: A printable recording media that contains a substrate, an ink receiving layer having a (WT)IR factor of less than 0.9 on the image side of the substrate, and a curvature control layer having a the (WT)CC of less than 0.6, on the backside side of the substrate. The printable recording media has an R value, (WT)IR/(WT)CC that is ranging from 1.6 to 3.0. The ink receiving layer and the curvature control layer include, at least, a single or multiple types of polymeric binders and, at least, a single or multiple types of inorganic pigment particles.

Abstract: Disclosed herein is a printable recording media including a substrate and, at least, an ink receiving layer that includes a first distinct layer and a second distinct layer that is applied on top of the first distinct layer. The first distinct layer includes an electrical charged substance and the second distinct layer includes, at least, a polymeric binder and nano-size inorganic pigment particles. Also disclosed herein is a method for making the printable recording media.