Conduent Business Services, LLC

Videoken, Inc.

Harish Arsikere

Eric Saund

Daniel Gureasko Bobrow

Daniel Davies

Margaret Helen Szymanski

Om Dadaji Deshmukh

Arijit Biswas

Prathosh Aragulla Prasad

Kyle D Dent

Jesse Vig

Kundan Shrivastava

Luke R Plurkowski

Arunasish Sen

Embodiments of the present invention provide a system for automatically extracting conversational structure from a voice record based on lexical and acoustic features. The system also aggregates business-relevant statistics and entities from a collection of spoken conversations. The system may infer a coarse-level conversational structure based on fine-level activities identified from extracted acoustic features. The system improves significantly over previous systems by extracting structure based on lexical and acoustic features. This enables extracting conversational structure on a larger scale and finer level of detail than previous systems, and can feed an analytics and business intelligence platform, e.g. for customer service phone calls. During operation, the system obtains a voice record. The system then extracts a lexical feature using automatic speech recognition (ASR). The system extracts an acoustic feature. The system then determines, via machine learning and based on the extracted lexical and acoustic features, a coarse-level structure of the conversation.

System for automatic extraction of structure from spoken conversation using lexical and acoustic features

The disclosed embodiments illustrate a method for classifying one or more audio segments of an audio signal. The method includes determining one or more first features of a first audio segment of the one or more audio segments. The method further includes determining one or more second features based on the one or more first features. The method includes determining one or more third features of the first audio segment, wherein each of the one or more third features is determined based on a second feature of the one or more second features of the first audio segment and at least one second feature associated with a second audio segment. Additionally, the method includes classifying the first audio segment either in an interrogative category or a non-interrogative category based on one or more of the one or more second features and the one or more third features.

Methods and systems for classifying audio segments of an audio signal

According to embodiments illustrated herein, a method and system is provided for indexing a multimedia content. The method includes extracting, by one or more processors, a set of frames from the multimedia content, wherein the set of frames comprises at least one of a human object and an inanimate object. Thereafter, a body language information pertaining to the human object is determined from the set of frames by utilizing one or more image processing techniques. Further, an interaction information is determined from the set of frames. The interaction information is indicative of an action performed by the human object on the inanimate object. Thereafter, the multimedia content is indexed in a content database based at least on the body language information and the interaction information.

Methods and systems for indexing multimedia content

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Harish Arsikere