19-08-2011, 10:32 AM
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ABSTRACT
An artificial passenger (AP) is a device that would be used in a motor vehicle to make sure that the driver stays awake. IBM has developed a prototype that holds a conversation with a driver, telling jokes and asking questions intended to determine whether the driver can respond alertly enough. Assuming the IBM approach, an artificial passenger would use a microphone for the driver and a speech generator and the vehicle's audio speakers to converse with the driver. The conversation would be based on a personalized profile of the driver. A camera could be used to evaluate the driver's "facial state" and a voice analyzer to evaluate whether the driver was becoming drowsy. If a driver seemed to display too much fatigue, the artificial passenger might be programmed to open all the windows, sound a buzzer, increase background music volume, or even spray the driver with ice water. One of the ways to address driver safety concerns is to develop an efficient system that relies on voice instead of hands to control Telematics devices.
One of the ways to reduce a driver’s cognitive workload is to allow the driver to speak naturally when interacting with a car system (e.g. when playing voice games, issuing commands via voice). It is difficult for a driver to remember a syntax, such as "What is the distance to JFK?""Or how far is JFK?" or "How long to drive to JFK?" etc.). This fact led to the development of Conversational Interactivity for Telematics (CIT) speech systems at IBM Research. CIT speech systems can significantly improve a driver-vehicle relationship and contribute to driving safety. But the development of full fledged Natural Language Understanding (NLU) for CIT is a difficult problem that typically requires significant computer resources that are usually not available in local computer processors that car manufacturer provide for their cars. To address this, NLU components should be located on a server that is accessed by cars remotely or NLU should be downsized to run on local computer devices (that are typically based on embedded chips).Some car manufacturers see advantages in using upgraded NLU and speech processing on the client in the car, since remote connections to servers are not available everywhere, can have delays, and are not robust. Our department is developing a “quasi-NLU”component - a “reduced” variant of NLU that can be run in CPU systems with relatively limited resources.
INTRODUCTION
US
Studies of road safety found that human error was the sole cause in more than half of all accidents .One of the reasons why humans commit so many errors lies in the inherent limitation of human information processing .With the increase in popularity of Telematics services in cars (like navigation, cellular telephone, internet access) there is more information that drivers need to process and more devices that drivers need to control that might contribute to additional driving errors
ER TECHNOLOGIES
ARTIFICIAL PASSENGER OVERVIEW
The AP is an artificial intelligence–based companion that will be resident in software and chips embedded in the automobile dashboard. The heart of the system is a conversation planner that holds a profile of you, including details of your interests and profession. When activated, the AP uses the profile to cook up provocative questions such “Who was the first person you dated?” via a speech generator and in-car speakers.
A microphone picks up your answer and breaks it down into separate words with speech-recognition software. A camera built into the dashboard also tracks your lip movements to improve the accuracy of the speech recognition. A voice analyzer then looks for signs of tiredness by checking to see if the answer matches your profile. Slow responses and a lack of intonation are signs of fatigue. If you reply quickly and clearly, the system judges you to be alert and tells the conversation planner to continue the line of questioning. If your response is slow or doesn’t make sense, the voice analyzer assumes you are dropping off and acts to get your attention.
The system, according to its inventors, does not go through a suite of rote questions demanding rote answers. Rather, it knows your tastes and will even, if you wish, make certain you never miss Paul Harvey again. This is from the patent application: “An even further object of the present invention is to provide a natural dialog car system that understands content of tapes, books, and radio programs and extracts and reproduces appropriate phrases from those materials while it is talking with a driver. For example, a system can find out if someone is singing on a channel of a radio station.
The system will state, “And now you will hear a wonderful song!” or detect that there is news and state, “Do you know what happened now—hear the following and play some news.” The system also includes a recognition system to detect who is speaking over the radio and alert the driver if the person speaking is one the driver wishes to hear.” Just because you can express the rules of grammar in software doesn’t mean a driver is going to use them. The AP is ready for that possibility: It provides for a natural dialog car system directed to human factor engineering for example, people using different strategies to talk (for instance, short vs. elaborate responses ). In this manner, the individual is guided to talk in a certain way so as to make the system work—e.g., “Sorry, I didn’t get it. Could you say it briefly?” Here, the system defines a narrow topic of the user reply (answer or question) via an association of classes of relevant words via decision trees. The system builds a reply sentence asking what are most probable word sequences that could follow the user’s reply.”
ABSTRACT
An artificial passenger (AP) is a device that would be used in a motor vehicle to make sure that the driver stays awake. IBM has developed a prototype that holds a conversation with a driver, telling jokes and asking questions intended to determine whether the driver can respond alertly enough. Assuming the IBM approach, an artificial passenger would use a microphone for the driver and a speech generator and the vehicle's audio speakers to converse with the driver. The conversation would be based on a personalized profile of the driver. A camera could be used to evaluate the driver's "facial state" and a voice analyzer to evaluate whether the driver was becoming drowsy. If a driver seemed to display too much fatigue, the artificial passenger might be programmed to open all the windows, sound a buzzer, increase background music volume, or even spray the driver with ice water. One of the ways to address driver safety concerns is to develop an efficient system that relies on voice instead of hands to control Telematics devices.
One of the ways to reduce a driver’s cognitive workload is to allow the driver to speak naturally when interacting with a car system (e.g. when playing voice games, issuing commands via voice). It is difficult for a driver to remember a syntax, such as "What is the distance to JFK?""Or how far is JFK?" or "How long to drive to JFK?" etc.). This fact led to the development of Conversational Interactivity for Telematics (CIT) speech systems at IBM Research. CIT speech systems can significantly improve a driver-vehicle relationship and contribute to driving safety. But the development of full fledged Natural Language Understanding (NLU) for CIT is a difficult problem that typically requires significant computer resources that are usually not available in local computer processors that car manufacturer provide for their cars. To address this, NLU components should be located on a server that is accessed by cars remotely or NLU should be downsized to run on local computer devices (that are typically based on embedded chips).Some car manufacturers see advantages in using upgraded NLU and speech processing on the client in the car, since remote connections to servers are not available everywhere, can have delays, and are not robust. Our department is developing a “quasi-NLU”component - a “reduced” variant of NLU that can be run in CPU systems with relatively limited resources.
INTRODUCTION
US
Studies of road safety found that human error was the sole cause in more than half of all accidents .One of the reasons why humans commit so many errors lies in the inherent limitation of human information processing .With the increase in popularity of Telematics services in cars (like navigation, cellular telephone, internet access) there is more information that drivers need to process and more devices that drivers need to control that might contribute to additional driving errors
ER TECHNOLOGIES
ARTIFICIAL PASSENGER OVERVIEW
The AP is an artificial intelligence–based companion that will be resident in software and chips embedded in the automobile dashboard. The heart of the system is a conversation planner that holds a profile of you, including details of your interests and profession. When activated, the AP uses the profile to cook up provocative questions such “Who was the first person you dated?” via a speech generator and in-car speakers.
A microphone picks up your answer and breaks it down into separate words with speech-recognition software. A camera built into the dashboard also tracks your lip movements to improve the accuracy of the speech recognition. A voice analyzer then looks for signs of tiredness by checking to see if the answer matches your profile. Slow responses and a lack of intonation are signs of fatigue. If you reply quickly and clearly, the system judges you to be alert and tells the conversation planner to continue the line of questioning. If your response is slow or doesn’t make sense, the voice analyzer assumes you are dropping off and acts to get your attention.
The system, according to its inventors, does not go through a suite of rote questions demanding rote answers. Rather, it knows your tastes and will even, if you wish, make certain you never miss Paul Harvey again. This is from the patent application: “An even further object of the present invention is to provide a natural dialog car system that understands content of tapes, books, and radio programs and extracts and reproduces appropriate phrases from those materials while it is talking with a driver. For example, a system can find out if someone is singing on a channel of a radio station.
The system will state, “And now you will hear a wonderful song!” or detect that there is news and state, “Do you know what happened now—hear the following and play some news.” The system also includes a recognition system to detect who is speaking over the radio and alert the driver if the person speaking is one the driver wishes to hear.” Just because you can express the rules of grammar in software doesn’t mean a driver is going to use them. The AP is ready for that possibility: It provides for a natural dialog car system directed to human factor engineering for example, people using different strategies to talk (for instance, short vs. elaborate responses ). In this manner, the individual is guided to talk in a certain way so as to make the system work—e.g., “Sorry, I didn’t get it. Could you say it briefly?” Here, the system defines a narrow topic of the user reply (answer or question) via an association of classes of relevant words via decision trees. The system builds a reply sentence asking what are most probable word sequences that could follow the user’s reply.”
