International Business Machines Corporation

Saurabh Mishra

Robert John Moore

Lei Huang

Eric Young Liu

Divyesh Jadav

Pawan Raghunath Chowdhary

Shun Jiang

Sunhwan Lee

Chung-hao Tan

Guangjie Ren

Techniques that facilitate a dialogue system based on contextual information are provided. In one example, a system includes a contextual information component and a dialogue routing component. The contextual information component determines contextual information associated with a user identity based on a statement related to communication information received by a computing device associated with the user identity. The dialogue routing component generates a path traversal for a dialogue system based on the contextual information to facilitate generation of a response to the statement by the dialogue system.

Dialogue system based on contextual information

A computer-implemented method of voice-to-text tagging for transcription of a human voice signal by one of an automatic speech recognition system, or a natural conversation, includes generating a speech-to-text verbal transcript of the verbal vocalizations of an audio signal at a verbal timestamp of the audio signal. A voice-to-text non-verbal transcript of the one or more non-verbal vocalizations of the audio signal is generated at a non-verbal timestamp of the audio signal. The non-verbal transcript and the verbal transcript are combined to generate an enhanced transcript.

System for voice-to-text tagging for rich transcription of human speech

One embodiment provides a method including receiving authoring conversational training data. A machine learning based conversational agent is trained with the conversational training data. The training includes: creating and storing example transcripts of user utterances, creating and storing example transcripts of agent utterances, sequencing utterance transcripts using the example transcripts of user utterances and the example transcripts of agent utterances, forming a corpus from the sequenced utterance transcripts, marking speech patterns that represent social actions from tagging the sequenced utterance transcripts, and forming a patterned corpus from the marked speech patterns.

Program dialog by example

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San Jose, CA, United States of America

Saurabh Mishra