Abstract: An example method involves (i) accessing first data defining multiple portions of a content item, wherein at least a plurality of the portions represent text; (ii) selecting, from the plurality of portions representing text, a subset of the portions representing text, wherein the selecting is based on each portion of the selected subset having a particular characteristic; (iii) based on the text represented by the portions of the selected subset, generating second data that represents a concatenation of the text represented by the portions of the selected subset; and (iv) providing output based on the generated second data.

Abstract: An example method involves (i) accessing first data representing text, wherein the text defines at least one position representing a particular type of grammatical break between two portions of the text; (ii) identifying, from among the at least one position, a position that is closest to a target position within the text; (iii) based on the identified position within the text, generating second data that represents a proper subset of the text, wherein the proper subset extends from an initial position within the text to the identified position within the text; and (iv) providing output based on the generated second data.

Abstract: An example method involves (i) accessing first data representing text, wherein the text defines at least one position representing a particular type of grammatical break between two portions of the text; (ii) identifying, from among the at least one position, a position that is closest to a target position within the text; (iii) based on the identified position within the text, generating second data that represents a proper subset of the text, wherein the proper subset extends from an initial position within the text to the identified position within the text; and (iv) providing output based on the generated second data.

Abstract: Driving data are collected from a vehicle by a device. The device comprises a vehicle interface for interfacing with an on-board diagnostics system of a vehicle and retrieving vehicle parameters of the vehicle from the on-board diagnostics system. The retrieved vehicle parameters include a vehicle identification parameter and driving parameters. The device includes a processor configured to identify the vehicle based on the vehicle identification parameter and determine data describing how the vehicle is driven based on the retrieved vehicle parameters. The device also includes an output interface configured to output the determined data.

Abstract: A personalized news service provides personalized news programs for its users by generating personalized combinations of audible versions of news stories derived from text-based based versions of the news stories. The audible versions may be generated from the text-based version by a text-to-speech system, or may by recording a person reading aloud the text-based version. To acquire recordings, the personalized news service can make a determination that a particular news story has a threshold extent of popularity. The news service can then transmit a request to a remote recording station for a recording of a verbal reading of the particular news story. The news service can then receive the requested recording from the remote recording station.

Abstract: A personalized news service provides personalized news programs for its users by generating personalized combinations of audible versions of news stories derived from text-based based versions of the news stories. The audible versions may be generated from the text-based version by a text-to-speech system, or may by recording a person reading aloud the text-based version. To acquire recordings, the personalized news service can make a determination that a particular news story has a threshold extent of popularity. The news service can then transmit a request to a remote recording station for a recording of a verbal reading of the particular news story. The news service can then receive the requested recording from the remote recording station.

Abstract: An example method involves (i) accessing first data defining multiple portions of a content item, wherein at least a plurality of the portions represent text; (ii) selecting, from the plurality of portions representing text, a subset of the portions representing text, wherein the selecting is based on each portion of the selected subset having a particular characteristic; (iii) based on the text represented by the portions of the selected subset, generating second data that represents a concatenation of the text represented by the portions of the selected subset; and (iv) providing output based on the generated second data.

Abstract: An example method involves (i) accessing first data representing text, wherein the text defines at least one position representing a particular type of grammatical break between two portions of the text; (ii) identifying, from among the at least one position, a position that is closest to a target position within the text; (iii) based on the identified position within the text, generating second data that represents a proper subset of the text, wherein the proper subset extends from an initial position within the text to the identified position within the text; and (iv) providing output based on the generated second data.

Abstract: An example method involves (i) accessing first data representing text; (ii) identifying a term within the represented text; (iii) using the identified term as a basis to select a text-editing rule from among a set of text-editing rules; (iv) generating second data that represents the represented text edited in accordance with the selected text-editing rule; and (v) providing output based on the generated second data.

Abstract: Disclosed computer-based systems and methods for analyzing a plurality of audio files corresponding to text-based news stories and received from a plurality of audio file creators are configured to (i) compare quality and/or accuracy metrics of individual audio files against corresponding quality and/or accuracy thresholds, and (ii) based on the comparison: (a) accept audio files meeting the quality and/or accuracy thresholds for distribution to a plurality of subscribers for playback, (b) reject audio files failing to meet one or more certain quality and/or accuracy thresholds, (c) remediate audio files failing to meet certain quality thresholds, and (d) designate for human review, audio files failing to meet one or more certain quality and/or accuracy thresholds by a predetermined margin.

Abstract: An example method involves determining an attribute of a user of a client device and selecting an audible version of a news story. The selection of the audible version of the news story is based on an association between the determined attribute and an attribute of the audible version of the news story. In the example method, the attribute of the audible version is indicative of an accent of the audible version of the news story. The method also includes generating a playlist for a personalized news program. The playlist includes a reference to the selected audible version of the news story. Further, the example method includes transmitting the generated playlist to the client device.

Abstract: A personalized news service provides personalized news programs for its users by generating personalized combinations of audible versions of news stories derived from text-based versions of the news stories. The audible versions may be generated from the text-based version by a text-to-speech system, or may by recording a person reading aloud the text-based version. To acquire recordings, the personalized news service can make a determination that a particular news story has a threshold extent of popularity. The news service can then transmit a request to a remote recording station for a recording of a verbal reading of the particular news story. The news service can then receive the requested recording from the remote recording station.