Merchant/consumer calls may be recorded and evaluated according to a variety of criteria. The call recordings and analyses thereof, as well as consumer tracking information, may be displayed in a user interface of a web-based online portal for convenience in evaluating the use and efficacy of marketing channels as well as the quality of merchant/consumer interactions. In an aspect, the user interface provides a representation of a variety of telephone calls as an interactive keyword cloud that presents business-value-specific keywords targeted for detection during such telephone calls. The keyword cloud may depict keywords in a range of colors, sizes, and relative positioning to connote varied degrees of significance, such as a relative rate of occurrence of keywords in the represented telephone calls. Each keyword in the keyword cloud may contain a hyperlink to related content such as a listing of telephone calls containing the keyword.

Merchant/consumer calls may be recorded and evaluated according to a variety of criteria. The call recordings and analyses thereof, as well as consumer tracking information, may be displayed in a user interface of a web-based online portal for convenience in evaluating the use and efficacy of marketing channels as well as the quality of merchant/consumer interactions. In an aspect, the user interface provides a representation of a variety of telephone calls as an interactive keyword cloud that presents business-value-specific keywords targeted for detection during such telephone calls. The keyword cloud may depict keywords in a range of colors, sizes, and relative positioning to connote varied degrees of significance, such as a relative rate of occurrence of keywords in the represented telephone calls. Each keyword in the keyword cloud may contain a hyperlink to related content such as a listing of telephone calls containing the keyword.

The artificial intelligence (AI)-based apparatus for controlling home-theater speech, which performs separation and synthesis on speech output from an electronic device of a user, includes an input unit that receives the speech, and a processor that separates and extract, from the speech from the input unit, a first signal representing a speech signal related to language or dialogue and a second signal representing a speech signal related to background sound or effect sound; extracts feature vectors of the first signal and the second signal to perform unsupervised learning; and calculates an amplitude difference between the first signal and the second signal according to a result of the unsupervised learning, and adjusting the amplitude difference according to an output method preset by the user.

The artificial intelligence (AI)-based apparatus for controlling home-theater speech, which performs separation and synthesis on speech output from an electronic device of a user, includes an input unit that receives the speech, and a processor that separates and extract, from the speech from the input unit, a first signal representing a speech signal related to language or dialogue and a second signal representing a speech signal related to background sound or effect sound; extracts feature vectors of the first signal and the second signal to perform unsupervised learning; and calculates an amplitude difference between the first signal and the second signal according to a result of the unsupervised learning, and adjusting the amplitude difference according to an output method preset by the user.

Methods, systems and apparatuses for computer-generated visualization of speech are described herein. An example method of computer-generated visualization of speech including at least one segment includes: generating a graphical representation of an object corresponding to a segment of the speech; and displaying the graphical representation of the object on a screen of a computing device. Generating the graphical representation includes: representing a duration of the respective segment by a length of the object and representing intensity of the respective segment by a width of the object; and placing, in the graphical representation, a space between adjacent objects.

Methods, systems and apparatuses for computer-generated visualization of speech are described herein. An example method of computer-generated visualization of speech including at least one segment includes: generating a graphical representation of an object corresponding to a segment of the speech; and displaying the graphical representation of the object on a screen of a computing device. Generating the graphical representation includes: representing a duration of the respective segment by a length of the object and representing intensity of the respective segment by a width of the object; and placing, in the graphical representation, a space between adjacent objects.

Techniques are disclosed relating to implementing user-created controls to modify music content. A music generator system may be configured to automatically generate output music content by selecting and combining audio tracks based on various parameters. Users may create their own control elements that the music generator system may train (e.g., using AI techniques) to generate output music content according to a user's intended functionality of a user-created control element.

Techniques are disclosed relating to implementing user-created controls to modify music content. A music generator system may be configured to automatically generate output music content by selecting and combining audio tracks based on various parameters. Users may create their own control elements that the music generator system may train (e.g., using AI techniques) to generate output music content according to a user's intended functionality of a user-created control element.

Techniques are disclosed relating to automatically generate new music content based on image representations of audio files. A computer system generate image representations of audio files. The image representations may be generated, for example, based on data in the audio files and MIDI representations of the audio files. Audio files for combination may then be selected based on analysis of the image representations. For example, image-based machine learning algorithms may be implemented to assess the image representations and select music for combining.

Techniques are disclosed relating to automatically generate new music content based on image representations of audio files. A computer system generate image representations of audio files. The image representations may be generated, for example, based on data in the audio files and MIDI representations of the audio files. Audio files for combination may then be selected based on analysis of the image representations. For example, image-based machine learning algorithms may be implemented to assess the image representations and select music for combining.