Spotify Ab

Sravana Reddy

Henriette Cramer

Rohit Kumar

Sarah Mennicken

Jennifer Thom-Santelli

Henrik Lindström

Rachel Malia Bittner

Andreas Jansson

Eric J Humphrey

Aaron Springer

Karl Humphreys

Robert L Williams

Philip Glenny Edmonds

Rosemary Ellen Jones

Matthew Joseph Kane

Ruth Brillman

Jussi Jerker Karlgren

Neha Kothari

Bryan Roy

Yongze Yu

A text-to-speech engine creates audio output that includes synthesized speech and one or more media content item snippets. The input text is obtained and partitioned into text sets. A track having lyrics that match a part of one of the text sets is identified. The location of the track's audio that contains the lyric is extracted based on forced alignment data. The extracted audio is combined with synthesized speech corresponding to the remainder of the input text to form audio output.

Text-to-speech from media content item snippets

A method includes retrieving a text from a database. The text corresponds to audio from a media content item that is provided by a media providing service, and the text includes a plurality of segments. The method also includes assigning a score for each segment in the text by applying the text to a trained computational model. The score corresponds to a predicted relevance of the respective segment to a narrative of the media content item. The method further includes identifying a non-narrative segment within the text using the assigned scores.

Systems and methods for detecting non-narrative regions of texts

A media content steering solution is provided to identify a user query to steer playback of media content that is currently playing or has been played. The user steering query can include a voice request for playing media content that is relatively different from the media content being currently played or having been played. The media content steering solution analyzes the utterance of the user query and uses it to identify such different content that satisfies the user intent contained in the user query.

Media content steering

Methods, systems, and related products that provide detection of media content items that are under-locatable by machine voice-driven retrieval of uttered requests for retrieval of the media items. For a given media item, a resolvability value and/or an utterance resolve frequency is calculated by a number of playbacks of the media item by a speech retrieval modality to a total number of playbacks of the media item regardless of retrieval modality. In some examples, the methods, systems and related products also provide for improvement in the locatability of an under-locatable media item by collecting and/or generating one or more pronunciation aliases for the under-locatable item.

System and method for assessing and correcting potential underserved content in natural language understanding applications

Term masking is performed by generating a time-alignment value for a plurality of units of sound in vocal audio content contained in a mixed audio track, force-aligning each of the plurality of units of sound to the vocal audio content based on the time-alignment value, thereby generating a plurality of force-aligned identifiable units of sound, identifying from the plurality of force-aligned units of sound a force-aligned unit of sound to be altered, and altering the identified force-aligned unit of sound.

Masking systems and methods

Term masking is performed by generating a time-alignment value for a plurality of identifiable units of sound in vocal audio content contained in a mixed audio track, force-aligning each of the plurality of identifiable units of sound to the vocal audio content based on the time-alignment value, thereby generating a plurality of force-aligned identifiable units of sound, identifying from the plurality of force-aligned identifiable units of sound a force-aligned identifiable unit of sound to be muddled, and audio muddling the force-aligned identifiable unit of sound to be muddled.

Growing community of inventors

Cambridge, MA, United States of America

Sravana Reddy