SUMMARIZATION AND/OR INDEXING OF PROGRAMS

Abstract: A method for the summarization and/or indexing of programs using transcript information includes the steps of furnishing (14) transcript information associated with the program, and processing the transcription information to obtain a summary and/or an index of the program. A preferred summarization method includes classifying (13) the type of program, determining a first cue to identify in the transcript information based on the classified type of program, identifying (16, 18) the first cue in the transcript information, storing a portion of the transcript information based on the first cue identified in the transcript information, and generating (20) a summary of the program based on the stored portion of the transcript information.

Description: Summarization and/or indexing of programs BACKGROUND INFORMATION Field of the Invention The present invention is directed to the summarization and/or indexing of programs, such as video. Description of the Related Art With the development and success of cable television, satellite television and internet-based technology, consumers have access to an ever-increasing number of television programs. In terms of high definition content, this amounts of over 200GB of information per day per channel. Therefore, it is becoming increasingly important for consumers to have the ability to quickly browse through the content description of live and stored television programs to enable the consumer to find a program or program segment that the consumer is most interested in viewing. The problem, however, is that the content of video programs is opaque. The current options for consumers are to either watch the entire video program at regular speed, fast forward through the entire video program to locate the portion of the program that is of interest, or to use EPG (electronic programming guide) data which provides only a very general program description of the program. OBJECTS AND SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a method and apparatus which provides summarization and indexing of programs, such as video programs. To this end, the invention provides a program summarization and/or indexing as defined in the independent claims. The dependent claims define advantageous embodiments using transcription information appeared to be particularly suitable to meet the object of the invention. In an advantageous embodiment, the present invention provides a method and apparatus which processes an incoming audio/data/video signal, extracts the transcript information from the audio/data/video signal, analyzes the transcript information, determines boundaries of commercial breaks and the end of the program, and provides a program summary, table of contents and a program index. In another advantageous embodiment, the present invention to provide a method and apparatus for the summarization and indexing of video programs using transcript information which overcomes inherent disadvantages of known video program information extraction and indexing methods. The above and other objects, features and advantages of the present invention will become readily apparent from the following detailed description thereof, which is to be read in connection with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS The sole figure is a block diagram of the system for summarization and indexing of video programs using closed-captioned text according to a preferred embodiment of the present invention; and DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT Referring to the figure, an apparatus for the summarization and indexing of programs using transcript information is shown. The term transcript information is intended to indicate text, for example closed-captioned text, which is typically provided with a video program's transmission (audio/data/video) signal and which corresponds to the spoken and non-spoken events of the video program or other textual source like EPG data. The transcript information can be obtained from video text or screen text (e.g., by detecting the subtitles of the video) and applying optical character recognition (OCR) on the extracted text such as that discussed in WO 01/37212 (attorneys' docket PHA 23^832) entitled "Video Stream Classification Symbol Isolation Method and System" filed November 17, 1999, and WO 01/37211 (attorneys' docket PHA 23.832) entitled "Symbol Classification with Shape Features Applied to a Neural Network", the entire disclosures of which are incorporated herein by reference. The present invention is based on the recognition that the transcript information is capable of being analyzed and searched using known searching techniques such as key- word searching and statistical text indexing and retrieval. Generally, the apparatus analyzes the transcript information of a program (audio, video, data and the like) and generates a program summary (which is used to provide a table of contents) and a program index. If the audio/data/video signal does not include a text portion, (i.e., it does not include transcript information) transcript information can be generated using known techniques such as a speech-to-text conversion as known in the art. The transcript information could also be obtained from a third party source, for example, TV Guide via the internet. The program summary and table of contents are designed to be reviewed by a user to determine whether or not to access (e.g., watch) a particular program. In addition, the program summary and table of contents can assist a user in identifying specific portions of a program which would be of interest. For example, for a video (i.e., television) program, the present invention monitors the transcript information of the audio/data/video signal and searches for specific cue words which indicate that a certain event which is worth noting in the program summary has occurred or will occur. After locating the cue words in the transcript information, the specific event is identified and information related to the event is extracted from the transcript information and a time stamp (a time of occurrence of the event during the broadcast of the program) is made. A certain event is worth noting if a user would make a decision as to whether or not to watch a program based upon the occurrence of the event. After the occurrence of each event, the relevant information extracted from the transcript information and the corresponding time stamp are stored. A program summary is generated and thereafter a table of contents is constructed which can be accessed by a user to determine what transpired during the program, and during what time portion of the program what events occurred. Therefore, if the program is stored/recorded in a memory device (e.g., analog or digitally stored on a videotape, disc, computer hard drive, etc.) the person who subsequently watches the program can view the program summary and/or table of contents generated for the program to determine if the program would be of interest to the user. If after reviewing the program summary or table of contents the user was interested in only viewing one portion of the program which was of interest, the user could proceed directly to the relevant portion of the program and therefore not waste time watching other segments which are not of interest to the user. It should be noted that the present invention is applicable to both structured and non-structured programs. Examples of structured programs include talk shows, news programs and sporting events. Structured programs have a specific format (e.g. for a talk show: monologue, commercial, first guest, commercial, second guest, commercial, last guest, commercial, end of show) and certain language is repeated during every program (e.g., the talk show host saying: "our first guest... please welcome"). An example of a non-structured program is a movie. For structured programs, a program summary, table of contents and program index can be created. However, for non-structured programs, only a program index is created. A preferred embodiment of the present invention will now be described. The apparatus 10 for the summarization of video programs using transcript information includes a video input port 12 for receiving an audio/data/video signal which preferably includes transcript information. Based on the received audio/data/video signal, a determination is made by a program type determiner 13 as to whether the program is "structured" or "non- structured". The program type determiner 13 preferably analyzes electronic programming guide (EPG) data (as known in the art) to determine the classification type of program (structured or non-structured) and whether the program is a talk show, news program, game show, or sporting event if the program is of the "structured" type. If EPG data is not available, it is foreseen that the program type determiner analyzes the transcript information and makes a comparison with known program formats to determine the classification type of the program. The classification type of the program is important because this determines the specific type of cues which will be searched for in the transcript information (as described in more detail below). That is, talk shows have one set of cues, news programs have another set of cues, etc. Also coupled to the video input port 12 is a transcript information extractor 14 which extracts the transcript information from the audio/data/video input signal. As mentioned previously, if the audio/data/video input signal does not include transcript information (e.g. closed-captioned text), then the transcript information can be generated using known speech-to-text generation techniques (or obtained from a third party source). Once the transcript information portion of the input signal is extracted, it is provided to a cue extractor 16 for analysis. The cue extractor 16 is coupled to a knowledge database 18 which contains a plurality of sets of cues, each set of cues being relevant to a particular classification type of program. The knowledge database is also coupled to the program type determiner 13 which provides the knowledge database with the type of the program. The knowledge database searches its database for the cues which correspond to the particular classification type of program. The knowledge database then provides the associated cues to the cue extractor. The cues are selected based on the known format of the program. The cue extractor monitors the transcript information for the occurrence of the cues provided by the knowledge database. The cues generally relate to sentences, phrases or words which indicate that some event is about to occur or has occurred in the program. For example in connection with a program which is classified by the program type determiner 13 as a talk-show, the knowledge database accesses the set of cues associated with a talk-show. The following is an example of the types of cues which are stored in the knowledge database for a talk show. Introduction cues: e.g. first guest, next guest... Intermediate cues: e.g. please welcome, the one the only... Bridging cues indicating a commercial: e.g. well be right back... Exit cues: e.g. good night folks, next week, thank you for watching... The knowledge database 18 instructs the cue extractor 16 to monitor the transcript information provided by the textual information extractor 14 for statements which indicate that an event is about to occur (such as "our first guest", "our next guest", "our second guest", "our third guest", or "our last guest", to indicate that a guest is being introduced). The knowledge database may also instruct the cue extractor to locate a second cue which indicates that the event is occurring (the guest is walking on stage). For example, the second cue might be "please welcome", "give a big round of applause to" and/or "the one and only". A temporal database 22 provides the cue extractor with information as to how close in time the first and second cues should be located. If the second cue is not identified within a specific predetermined time after identification of the first cue, the apparatus determines that the first cue was improperly identified or that the second cue was missed. Therefore, the knowledge database instructs the cue extractor to identify new set of first and second cues. However, if the second cue is identified within the specific predetermined time period, then the textual information proximate the first and second cues is stored in memory and, as explained below, provided to an inference engine 20 to extract relevant information and to make inferences based on the textual information (for a talk show the inferences include the identity and field of renown of the guest). The fact that the first and second cues have been located in the textual information is provided to the inference engine 20. The inference engine obtains from the cue extractor 16 not only the fact that the first and second cues were located but also the textual information proximate the first and second cues. The inference engine 20 analyzes the portions of the transcript information identified and provided by the cue extractor so as to extract specific information and make inferences therefrom ( for example, the name of the guest and the field of renown). In a preferred embodiment, the inference engine 20 has associated therewith a look-up table which correlates the occurence of specific words in the transcript information to specific areas/topics. For example, if the transcript information related to the first and second cues (which indicate that an event will or has occurred) includes words such as actor, actress, glamour, star, film, Oscar or thriller, the inferences engine (after accessing the look-up table) correlates these words to the movie industry. An inference is made that the guest is in the movie industry. In order to determine the guest's name, the inference engine may, for example, search for words such as "please welcome" and extract the words or name that follows. The extracted words may be compared to a database of names (e.g., celebrities and other well- known names) to check that the correct words (name) were extracted. If a valid name was not extracted, then additional searching of the transcript information occurs to identify the proper name. Similar extraction of transcript information and inferences can occur for other facts related to the guest. The name and area of renown were deemed to be most useful for generating a summary and table of contents. The cue extractor 16 then accesses the knowledge database 18 to determine what cue, if any, it should identify next. Upon receiving the instruction from the knowledge database 18 based on the type of program that was identified, the cue extractor searches the transcript information for the next new cue. A second new cue might or might not be. required depending upon the classification of the program (for example, if the program is a hockey game, it is foreseen that the cue extractor would monitor the transcript information for only one word, "score" or "goal", and extract the transcript information which occurs proximate the identified word). After identification of the next cue, the inference engine and temporal database are accessed as described above until an end of the program is detected. The information (e.g., name and area of renown) extracted from the transcript information by the inference engine 20 is stored in memory (not shown) along with the corresponding time stamp. The information obtained from the inference engine is organized into a program summary and table of contents of the program. In a preferred embodiment, the program summary is generated by inserting the name and area of renown of each guest into predetermined text, such as: "The first guest was (insert guest's name) whose specialty is in the field of (insert guest's area of renown)". The following is an example of a program summary for a talk show which includes the predetermined and/or inferred text and the transcript information which occurs between the first and second cues. There were 3 guests in the talk show. The first guest was Adam Sandier whose specialty is in the field of music. My first guest tonight is one of the biggest film stars around. He's here tonight to perform a song off his new cd, "Stan and Judy's kid." Go out and buy it. He's really hurting. The second guest was Peta Wilson from the field of movie. My next guest tonight stars as the grungy street punk turned glamorous secret agent assassin in the USA network's "La Femme Nikita." The last guest was Chris Eigeman who has made a livelihood in the field of movie. My next guest this evening has starred in some pretty cool films. He's been in "Metropolitan", "Barcelona" and "The Last Days of Disco". He can now be seen on the show "It's like, you know" on ABC. After generation of the program summary, a table of contents is generated for the program. The table of contents preferably includes the relevant event information for the program and the time offset into the program when the event occurred. For example, if the program is a talk show, the table of contents will include the name of each guest, the area of renown of the guest and the time during the program that each guest appeared. The following is an example of a table of contents for a talk show: Jay Leno host - minutes 1-14 Adam Sandier music - minutes 15-29 Peta Wilson movie - minutes 30-44 Chris Eigeman movie - minutes 45-60. The table of contents may also include any other extracted information such as the occurrence of commercials or topics of conversation. Concurrent to analysis of the transcript information to create the program summary and table of contents, a program index is created. In one embodiment, the cue extractor 16 notes the occurrence of words in the transcript information and provides the information to the knowledge database 18 and inference engine 20 which include a look-up table to associate specific words with specific topics. The transcript information may be monitored for a predetermined period of time and the topic which is associated with the most words is indicated as the topic for the corresponding time period. It is also foreseen that the program index may list all of the "non-stop" words used in the program, and provide the corresponding times during the program that the words were used. "Non-stop" words are words other than "stop" words. Some examples of "stop" words are "and", "or", "then", "if", "are", "to", and "when". The method of the present invention can be described as follows. Initially an audio/data/video signal is received. The audio/data/video signal preferably includes among other things a transcript information signal which is extracted therefrom. Thereafter, using known methods such as scanning the corresponding EPG signal or analyzing the transcript information, the classification type of the program (structured or non-structured) is determined. If the classification type of the program is structured, the program structure may also be identified as, for example, a talk show, news program, game show, or sporting event, among others. Based on the classification type of the program, a specific set of cues will be sought in the transcript information (closed-captioned text) based on domain knowledge about the structure of the program (i.e., the way the program segments are structured). For example, a talk show has segments for each of the guests. A sports program has segments that can be based on known portions of the game (i.e., periods for hockey, quarters for basketball and football, innings for baseball and sets for tennis) or on events during the game (i.e., scoring). In order to summarize a hockey game into meaningful segments, the cues might include words such as "score" and "goal" so that a scoring summary of the game could be obtained. If the program is a talk show, cues such as "first guest", "next guest", "second guest", "last guest", and "please welcome" would be identified in the transcript information to identify not only program segments, but program events. The program segments are used when the table of contents is generated to segment the program into identifiable portions wherein specific events have occurred. After the cues which are being sought are determined, the transcript information is monitored for the occurrence of a first cue. When the first cue is identified in the transcript information, the time of the program at which the first cue was identified is noted. Then a determination is made as to whether the end of the program was reached. If the end of the program is not reached, then the transcript information is monitored for the occurrence of the second cue. This case is searched for in the transcript information for a limited time period based on rules generated regarding the known structure (format) of the program that the second cue should occur within a specific period of time of occurrence of the first cue. The limited time period is obtained from a look-up table which associates the first and second cues. The look-up table indicates the maximum allowable time separation during the program between the identification of the first and second cues. This information is provided by, for example, the temporal database 22 as previously explained. This temporal check is performed to eliminate potential errors in associating events which should not be associated together. For example in connection with a talk show, it is known that talk show hosts typically introduce a guest by identifying the guest's area of renown and notoriety. The guest is then brought on stage within a relatively short period of time (less than 1 minute). If, however, there is a separation of more than 1 minute (e.g., 10 or 20 minutes) between the identification of the first cue (i.e., "Our next guest...") and the second cue (i.e., "Please welcome..."), then there probably was an error in identifying the first or second cue. Therefore an inference is made that the identification of the first cue and that of the second cue are not related. If the second cue is not identified within the specific predetermined time period, then the method checks to see if a commercial is detected, notes the time of the commercial in the program, and checks to see whether the end of the program is detected. The commercial and end of program detection can occur via cues provided by the knowledge database (as explained above) or any other known means of commercial and end of program detection such as those disclosed in WO 01/28240 (attorneys' docket PHA 23.803) entitled Automatic Signature-Based Spotting, Learning and Extracting of Commercials and Other Video Content, and US 6,100,941 (attorneys' docket PHA 23.477) entitled Apparatus and Method for Locating a Commercial Disposed Within a Video Stream, the entire disclosures of which are incorporated herein by reference. When the second cue is identified, the time of the program at which the second cue is identified is noted. If the program has ended, the method proceeds as explained below. If the program has not ended, the method returns to the step wherein new first and second cues are determined. If the second cue is identified within the predetermined time period, then an inference is made from the first and second cues. That is, the transcript information proximate the portion of the transcript information where the first and second cues were identified is analyzed to extract information regarding the cues (e.g., information concerning the first talk show guest). Examples of the information that is extracted from the transcript information for a talk show include the name, area of renown, and current projects of the guest. This information is stored in memory (not shown). In addition, the time of occurrence of the associated event during the program is noted for inclusion in the table of contents so that a user of the system will be able to identify at what point in the program a particular event occurred. It is also foreseen to extract a representation (e.g., audio or video clip) associated with the information extracted from the transcript information related to the first and second cues. The representation can be used in conjunction with the information extracted from the transcript information related to the first and second cues when creating the program summary and table of contents. Therefore, a user would not only be able to see a list of events which occurred during a program and the times during the program when the events occurred, but the user would also be able to see a visual representation of the event or hear an audio clip of the event. As a result, the user is aided in making a determination as to whether that particular portion of the program should be viewed. Thereafter, the method monitors the transcript information to determine if a commercial break has occurred (Step 58). The commercial detection can occur via cues provided by the knowledge database (as explained above). If a commercial is detected, the time of the commercial during the program is noted and stored, (for example, to indicate an end of one segment of the program and the beginning of another segment). Then a determination is made as to whether the program has ended. The end of the program is determined in a manner similar to that set forth above for detecting commercials. Specifically, the closed-captioned text may be monitored for phrases such as "next week", "thank you", and "goodnight", for a talk show. Other known end of program detection methods can be employed such as that disclosed in PCT/EPO 1/00309 (attorneys' docket PHUS000034) entitled Method and Apparatus for Recording Programs Prior to or Beyond Present Time Period, the entire disclosure of which is incorporated herein by reference. If the end of the program is not detected, then the method returns to wherein new first and second cues are determined. If the end of the program is detected, the information extracted from the transcript information in is stored in memory in chronological order with the corresponding time stamp and a representation (e.g. audio/video) for access by a user. A program summary is generated using the extracted information and a table of contents is produced from the information contained in the program summary as explained above. Thereafter the method ends. It should be specifically mentioned again that concurrent to the detection of cues in the transcript information, the present invention generates a program index of the transcript information of the video program which is independent of the program summary and table of contents. In a preferred embodiment, the present invention monitors the textual information for the occurrence of specific words during the program. The present invention includes a look-up table which associates words identified in the text with particular topics. The following is an example of some of the topics and associated words. Movie > Actor, actress, glamour, Hollywood, stars, film, Oscar, academy award, thriller, movie, talent. Music > Singer, Song, Album, solo, record, pop, vocal, cd, voice, music, perform, talent. Politics > republican, democrat, president, senator, foreign, policy, election, vote, prime minister, leader, politics. The program index lists the topics associated with the words most often mentioned during the program and the time during which the topics occur. The program index can be used as a reference by a user to determine if a particular topic was discussed during the program. Alternatively, the program index contains a list of the words used during the program and the portion of the program where the words were used. The word or topic index can be generated using known word and topic extracting methods, such as key-word searching and statistical text indexing and retrieval. Moreover, the program index can be a reformulated table of contents for the program. For example, when the table of contents is: David Letterman 00:00 to 12:15 politics 1:42 7:15 thanksgiving 7: 15 9:30 model 9:30 12:15 Guest 1: Michelle Pfeiffer 16:17 to 23:00 ...(similar to above) Commercial 2:23:01 to 28:00 Guest 2: Ethan Hawk 28:01 to 28:15 Commercial 3:38:16 to 44:00 Guest 3: Joni Mitchell 44:01 to 59:00 ...(similar to above) End: 59:01 to 60:00 and the resulting program index is an alphabetical list of names followed by topics: David Letterman 00:00 to 12:15 Ethan Hawk 28:01 to 38:15 Joni Mitchell 44:01 to 59:00 Michelle Pfeiffer 16:17 to 23:00 model 9:30 12:15 politics 2:42 7:15 thanksgiving 7:15 9:30. Although the present invention has been discussed above in relation to talk shows, the invention is applicable to any type of program. However, the invention is most suited for use with highly structured programs like talk shows, news programs, game shows and sporting events which have a known format and repeat specific phrases in every show which are then followed by relevant information, (i.e., "our top story tonight...", "our first guest..."). The apparatus according to the present invention may be contained within a television, in a set-top box or a stand-alone device coupled to an audio/data/video signal processor, or other viewing device (e.g., computer). The method could also be provided as a service applied to any database of video/audio programs or from the internet. While the present invention is described in the context of its use with television broadcast signals, it is foreseen that the system can be utilized with audio processors (i.e., radios) to provide for example, a song index, computers that have internet accessibility so as to scan internet-based signals, video streaming, audio streaming or any stored content to create textual information which can be searched and processed in accordance with the present invention. Having described specific preferred embodiments of the invention with reference to the accompanying drawings, it will be appreciated that the present invention is not limited to those precise embodiments and that various changes and modifications can be affected therein but one of ordinary skill in the art without departing from the scope of the invention defined by the appended claims. For example, it is foreseen that the cues that are searched for can be altered by the user to suit the user's specific needs, and that the cues can be learned (e.g., using artificial intelligence) by the system based on recurring textual information for a specific type of program. It is also foreseen that multiple cues can be searched for concurrently and that the invention is not limited to searching for one cue at a time. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the device claim enumerating several means, several of these means can be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

Claims: CLAIMS: 1. A method for the summarization of a program, the method comprising the steps of: furnishing (14) transcript information associated with the program; classifying (13) the type of program; determining (16) at least a first cue of a plurality of cues to identify in the transcript information based on the classified type of program; identifying (16, 18)the at least first cue in the transcript information; storing a portion of the transcript information based on the at least first cue identified in the transcript information; and generating (10) a summary of the program based on the stored portion of the transcript information. 2. The method for summarization of a program according to claim 1 further comprising the step of: noting a time, relative to a beginning of the program, that the at least first cue is identified in the transcript information. 3. The method for summarization of a program according to claim 1 further comprising the steps of: determining (116) at least a second cue of the plurality of cues to identify in the transcript information based on the type of program; determining (22) a maximum time period to search for the at least second cue; identifying (16) the second cue in the transcript information; and determining (16, 22) whether the at least second cue was identified in the transcript information prior to expiration of the maximum time period, wherein if the at least second cue was not identified in the transcript information prior to expiration of the maximum time period, defining and identifying new at least first and at least second cues in the transcript information. 4. The method for summarization of a program according to claim 3 further comprising the steps of: noting a time, relative to a beginning of the program, that the second cue is identified in the transcript information. 5. The method for summarization of a program according to claim 3 further comprising the steps of: extracting data from the transcript information based on identification of at least one of the at least a first cue and the at least a second cue in the transcript information; and using the extracted data and the classified type of program to generate the summary of the program. 6. The method for summarization of a program according to claim 5 further comprising the steps of: receiving an audio/data/video signal associated with the program; analyzing the audio/data/video signal to identify and extract at least one of a visual or audio representation associated with the extracted data; and associating the at least one of a visual or audio representation with the summary of the program. 7. The method for summarization of a program according to claim 3 wherein at least one of the plurality of cues correspond to specific words, phrases or sentences to be identified in the transcript information. 8. The method for summarization of a program according to claim 1 wherein the step of classifying the type of program further comprises the step of: analyzing at least one of electronic program guide (EPG) data, pictorial information, audio information and the transcript information. 9. The method for summarization of a program according to claim 3 wherein the at least first cue and the at least second cue are selected from a database (18) based on the classified type of program. 10. The method for summarization of a program according to claim 5 wherein the data extracted from the transcript information is proximate the identified at least a first cue and at least a second cue and based on knowledge regarding the structure of the program. 11. The method for summarization of a program according to claim 15, wherein the program is a talk show, and wherein the extracted information is at least one of a name of a guest, a field in which the guest is known, and the time period during the video program during which the guest appears. 12. The method for summarization of a program according to claim 1, further comprising the steps of: determining at least one further cue to identify in the transcript information, the at least one further cue being selected from a database based on the classified type of the program; and identifying the at least one further cue in the transcript information. 13. Apparatus for summarization of a program using transcript information, comprising: an audio/data/video input port (12) for receiving an audio/data/video signal; a program type detector (13) which identifies a generalized type category of the program based on the received audio/data/video signal; a transcript information extractor (14) operatively coupled to the audio/data/video input port which provides transcript information corresponding to the program; a cue database (18) which stores a plurality of groups of cues, each of the plurality of groups of cues being associated with one generalized type category of program and including a plurality of cues which are to be identified in the transcript information; and a cue extractor (16) operatively coupled to the transcript information extractor (14) for receiving the transcript information from the transcript information extractor, the cue extractor(16) also being operatively coupled to the cue database (18) and receiving an instruction from the cue database (18) based on the generalized type category of the program identified by the program type detector (13) as to what cues to identify in the transcript information, the cue extractor (16) identifying a portion of the transcript information which corresponds to at least one cue of the plurality of cues of the identified generalized type category. 14. Apparatus for summarization of a program according to claim 13 wherein the cue extractor (16) also identifies a time with respect to a beginning of the program wherein the at least one cue is identified. 15. Apparatus for summarization of a program according to claim 13, wherein the cue extractor (16) identifies portions of the transcript information associated with the at least one cue and a second cue respectively, and wherein the cue extractor indicates first and second time stamps corresponding to the time of identification of the at least one cue and the second cue during the program. 16. Apparatus for summarization of a program according to claim 13 further comprising: a temporal database (22) operatively coupled to the cue database (18), the temporal database (22) storing a plurality of timing rules relating to time periods in which if the at least one cue is identified in the transcript information, the second cue should appear within a specific time period; and an inference engine (20) operatively coupled to both the temporal database (22) and the cue extractor (16), the inference engine (20)receiving the portion of the transcript information identified by the cue extractor (16) as corresponding to the at least one cue and second cue, the inference engine (20) also receiving the plurality of timing rules, the inference engine (20) applying at least one of the plurality of timing rules to determine if the identification of the portions of the transcript information with respect to the at least one cue and second cue is proper, the inference engine (20) also receiving the transcript information and extracting information based on the identification of at least one of the portions of the transcript information by the cue extractor; and a memory for storing the information extracted by the inference engine. 17. Apparatus for summarization of a program as defined by claim 13, wherein the transcript information is one of closed-captioned text obtained from the audio/data/video signal, speech-to-text, subtitles or textual information corresponding to the video program obtained from a third party source. 18. A method for indexing a program, the method comprising the steps of: furnishing transcript information associated with the program, the transcript information including a plurality of words; monitoring the transcript information to note the occurrence of particular words; and noting a time during the program corresponding to the occurrence of the particular words; associating the particular words and the time during the program that the particular words occurred. 19. The method for indexing a video program as defined by claim 18 further comprising the steps of: relating the occurrence of the particular words to one of a plurality of topics; and associating the plurality of topics and the time during the video program that the particular words occurred. 20. A method of summarizing and/or indexing a program, the method comprising: furnishing transcript information associated with the program; and processing the transcript information to obtain a summary and/or an index of the program.

Inventors: AGNIHOTRI LALITHA, DEVARA KAVITHA V, DIMITROVA NEVENKA, AGNIHOTRI, LALITHA, DEVARA, KAVITHA, V., DIMITROVA, NEVENKA
Applicants: KONINKL PHILIPS ELECTRONICS NV, KONINKLIJKE PHILIPS ELECTRONICS N.V.
Application year: 2001
Main classification: H04N7
IPC codes: G06F17, H04N5, H04N7