Abstract: Different types of media experiences can be developed based on characteristics of the consumer. “Linear” experiences may require execution of a pre-built script, although the script could be dynamically modified by a media production platform. Linear experiences can include guided audio tours that are modified or updated based on the location of the consumer. “Enhanced” experiences include conventional media content that is supplemented with intelligent media content. For example, turn-by-turn directions could be supplemented with audio descriptions about the surrounding area. “Freeform” experiences, meanwhile, are those that can continually morph based on information gleaned from a consumer. For example, a radio station may modify what content is being presented based on the geographical metadata uploaded by a computing device associated with the consumer.

Abstract: Introduced here are computer programs and associated computer-implemented techniques for discovering the presence of filler words through tokenization of a transcript derived from audio content. When audio content is obtained by a media production platform, the audio content can be converted into text content as part of a speech-to-text operation. The text content can then be tokenized and labeled using a Natural Language Processing (NLP) library. Tokenizing/labeling may be performed in accordance with a series of rules associated with filler words. At a high level, these rules may examine the text content (and associated tokens/labels) to determine whether patterns, relationships, verbatim, and context indicate that a term is a filler word. Any filler words that are discovered in the text content can be identified as such so that appropriate action(s) can be taken.

Abstract: Introduced here are computer programs and associated computer-implemented techniques for discovering the presence of filler words through tokenization of a transcript derived from audio content. When audio content is obtained by a media production platform, the audio content can be converted into text content as part of a speech-to-text operation. The text content can then be tokenized and labeled using a Natural Language Processing (NLP) library. Tokenizing/labeling may be performed in accordance with a series of rules associated with filler words. At a high level, these rules may examine the text content (and associated tokens/labels) to determine whether patterns, relationships, verbatim, and context indicate that a term is a filler word. Any filler words that are discovered in the text content can be identified as such so that appropriate action(s) can be taken.

Abstract: Different types of media experiences can be developed based on characteristics of the consumer. “Linear” experiences may require execution of a pre-built script, although the script could be dynamically modified by a media production platform. Linear experiences can include guided audio tours that are modified or updated based on the location of the consumer. “Enhanced” experiences include conventional media content that is supplemented with intelligent media content. For example, turn-by-turn directions could be supplemented with audio descriptions about the surrounding area. “Freeform” experiences, meanwhile, are those that can continually morph based on information gleaned from a consumer. For example, a radio station may modify what content is being presented based on the geographical metadata uploaded by a computing device associated with the consumer.

Abstract: Media content can be created and/or modified using a network-accessible platform. Scripts for content-based experiences could be readily created using one or more interfaces generated by the network-accessible platform. For example, a script for a content-based experience could be created using an interface that permits triggers to be inserted directly into the script. Interface(s) may also allow different media formats to be easily aligned for post-processing. For example, a transcript and an audio file may be dynamically aligned so that the network-accessible platform can globally reflect changes made to either item. User feedback may also be presented directly on the interface(s) so that modifications can be made based on actual user experiences.

Abstract: Different types of media experiences can be developed based on characteristics of the consumer. “Linear” experiences may require execution of a pre-built script, although the script could be dynamically modified by a media production platform. Linear experiences can include guided audio tours that are modified or updated based on the location of the consumer. “Enhanced” experiences include conventional media content that is supplemented with intelligent media content. For example, turn-by-turn directions could be supplemented with audio descriptions about the surrounding area. “Freeform” experiences, meanwhile, are those that can continually morph based on information gleaned from a consumer. For example, a radio station may modify what content is being presented based on the geographical metadata uploaded by a computing device associated with the consumer.

Abstract: Media content can be created and/or modified using a network-accessible platform. Scripts for content-based experiences could be readily created using one or more interfaces generated by the network-accessible platform. For example, a script for a content-based experience could be created using an interface that permits triggers to be inserted directly into the script. Interface(s) may also allow different media formats to be easily aligned for post-processing. For example, a transcript and an audio file may be dynamically aligned so that the network-accessible platform can globally reflect changes made to either item. User feedback may also be presented directly on the interface(s) so that modifications can be made based on actual user experiences.