SoundHound, Inc. (Santa Clara, CA)

Agents engage and disengage with users with a degree of intelligence. Users can inform agents to stay engaged without requiring the use of a wakeword. Engaged states are able to support modal dialogs, barge-in, and other features. Users can cause disengagement explicitly. Disengagement can be conditioned on user change, timeout or other conditions in the environment. Engagement may be continuous or one-time. Recurrent states can be locked or attentive. Conditional or unconditional locks are able to be designed to ensure user continuity. The continuity of users can be checked by comparing parameters or following the users with a variety of methods, such as cameras, microphone arrays and other sensors.

Virtual assistants, also known as virtual agents, are computer-based systems that can carry out natural language conversations with users. The agent usually provides services to a human user. It reacts (or attempts to respond) to natural languagerequests from users, such as inquiries for information or requests for action, by using a combination of software and hardware.

The concept of a virtual assistant is anthropomorphic. Common assistants like Siri, Alexa, Cortana, Nina, and others include human-like names, people-like voices, and maybe personalitiesor personalities’ of some kind. Users are encouraged to interact in anatural way with assistants as if they were partners in a human conversation. The assistant is a communication interface that is understandable to the user and blocks out of the view of the entire system whose internal workings can be extremely complex. The notion of engagement is the primary element of human-machine interaction. An agent is considered engaged when it responds to the user’s requests.

An Interactive Voice Response (IVR) system allows a user to speak to the virtual assistant via a telephone line. They are engaged in conversation. The assistant listens , and then processes (or attempts to take in) every word spoken by the user.

In more open situations speaking by a user can be directed to a individual in the room or to an agent virtual. As the agent reacts to the user’s voice and is engaged in a dialogue. If the agent is actively engaged and the user’s language is not intended for the agent, a negative behaviour could result. It’s possible for the agent to give annoying or sloppy answers. The agent could take an action that the user wasn’t planning and cause unintended consequences.

This is a signpost to a problem that has been identified in the design of user interfaces as the King Midas effect. The cause is the inability of users to stop the consequences of their interaction. The legend says that King Midas was greedy, and he wished to transform everything that he touched to gold. This was a curse as his wish was actually granted. He kissed his daughter and she turned into an image of gold. The food he ate also changed to gold as he was able to touch it.

For a more concrete example of the King Midas effect, suppose an agent is told, “Get me an Uber to SFO for 8 pm” and acts on the request correctly by accessing Uber to place an order. The agent might remain engaged when the customer asks her daughter “Can you bring me my red shoes from your closet, dear,” but she may reply with a dull response (“I don’t understand what you’re saying”) or an even more humorous one (“You called darling! . . I also like you”) or a pragmatic one (“which closet?”) However, none of these responses are appropriate. Although the request was addressed to the child of the user no response was expected by the agent. If the Uber request had been sent after the agent was asleep, this problem could be prevented. It is imperative to avoid the King Midas effect.

To stop an agent from responding to user requests during unintentional times, conventional agents disengage the agent after each request. After serving a request that the agent is unable to accept any new requests until it is required to re-engage. The user has to “wake up the agent” prior to any other request can be considered. The most common method of waking an agent is to say “Hey Siri”, “OK Google,” or “Alexa”. It can be either a single word or a phrase with multiple words. Pushes, taps , and clicks are different ways of waking up an agent. However, these can be accomplished manually.

The word “wake” is not mandatory. It’s used to attract the attention of the agent. It creates overhead, which is a waste of time when compared to regular communication between people. The equivalent of a”wakeword” is only utilized in specific situations, such as calling a specific person’s attention or switching the recipient of an exchange.

It’s inefficient and time-consuming to repeat a wakeword for each request. This is known as “wakeword fatigue”. It is a fact that people have accepted the need the fact that they have to wake their agents, every time, for lack of an alternative.

The well-known method of avoiding the King Midas effect has the price of a large amount. This makes man-machine dialogues difficult to understand, inefficient and tired. It also creates poor user experiences. Methods to facilitate natural, fluid and effective communication between humans and virtual agents are required.

This disclosure aims to enhancements in the efficiency and fluidity of man-machine dialog over current methods. Methods that don’t cause wakeword fatigue, and therefore avoid the King Midas Effect, are a way to address this problem. These engagement policies that aren’t traditional, have one common purpose: to lessen or eliminate the need for agents to be “waked up” prior to each request. There are several engagement policies which can be made public in order to make the conversation between man and machine more natural and effective.

Users have full control over the behavior of agents using locking engagement rules. With these policies, spoken requests or event indicators can cause an agent to enter the locked engagement, a state where the agent is engagedand able to process requests repeatedly until explicitly unlocked. Locked engagement is not necessarily unconditional; this is a very important case because, despite its simplicity, it goes far in reducing the fatigue of wake words. Unconditional locked engagementallows an undetermined number of requests to be handled without any wake-up signals until the user decides to let the agent out of its state. A variant of locked engagement lets the user specifying specific conditions for engagement, such aswho can engage, and when. A further variant of conditional locking engagement is to reserve the agent’s attention to a specific user (to the exclusion of other users) for a revolving period of time; there is no overhead for communication. Both unconditional locking, and reserved engagement are practical and easy solutions for getting rid of wakeword fatigue.

The “Attentive Agent”, another engagement policy, makes use of the agent’s intelligence to make autonomous decisions about engagement or disengagement. It is based on the agent?s perception of the situation and the user and a model for human-like interaction. An attentive agent remains active as long as it believes that the user would like to be engaged; it has to pay attention and be able, like people involved in a natural human conversation to make use of various indicators to determine the moment in time, whether the user wants to keep engaging. Finally the hybrid policy is defined, that integrate the policy of locked engagement with the attentive agent policy.

The applications range from intelligent assistants, through speech-enabled devices of all types, including isolated interne of things (IoT) devices, to intelligent spaces with potentially many sensors and effectors, such as automobiles,intelligent homes, offices, stores and shopping malls, and humanoid robots.

Click here to view the patent on USPTO website.


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