SK500702014A3 - Method to lower decline in watching channels during commercial breaks and a connection - Google Patents

Abstract

In a way to reduce channel audience slippage during ad breaks in a single stream direction, the currently selected channel is recognized from the audio sample from the TV scanned by the mobile platform, and locked special content is brought to the mobile ad on the mobile platform in the second direction. Opening special content to a mobile TV ad is available at the start of an ad break while continuing to track the same selected channel. The system engagement to reduce channel view overflow during advertising breaks consists of a sample server (1) with input (2) from the sources of broadcasting TV signals, further comprising a content server (3) that is connected to the mobile platform (4) with a two-way wireless link control application. There is also a recognition server (5) that is linked to both the sample server (1) and the content server (3). The content server (3) includes a first information block (6) with special content for television advertising and also a second information block (7) with aggregated relevant content on social networks.

Description

Annotation:

In a method for reducing channel slump during advertising breaks in one direction of transmission, the currently selected channel is recognized from the audio sample from the TV captured by the mobile platform, and in the other direction of transmission, the locked special content for the television advertisement. Opening special TV ad content on the mobile platform is available at the beginning of the advertising break while continuing to watch the same selected channel. The system connection to reduce channel slump during advertising breaks consists of a sampling server (1) with input (2) from TV broadcasting sources, further comprising a content server (3), which is wirelessly connected to a mobile platform (4) with control application. There is also a recognition server (5) that is connected to the sampling server (1) and also to the content server (3). The content server (3) comprises a first information block (6) with special content for television advertising and also a second information block (7) with aggregated relevant content on social networks.

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A way to reduce channel spillover during advertising breaks and engagement

Technical field

The invention relates to a method for reducing the overflow of channel ratings during advertising breaks and to engaging in the method. The invention falls within the field of telecommunications and advertising technology.

BACKGROUND OF THE INVENTION

In the state of the art, there are standard advertising systems for displaying advertising spots or banners in electronic devices such as TVs. The ad is paid by the advertiser and there is no response to the ad's appearance until the end. Failure to see an ad to the end significantly reduces the effect of the ad on the ad visitor. In addition, one of the biggest problems and sources of economic loss for TV broadcasters is the drop in viewership of their channels during advertising breaks. The viewers tend to switch to another channel, leave the screen and stop watching TV or TV. they are not within reach of TV sets at this time. The aforementioned unfavorable facts have led to efforts to develop a concept of such an advertising system for TV which would ensure that the channels of viewers of their channels were maintained during advertising breaks, which would at the same time control the appearance of advertising spots for the advertiser. In particular, this concept would require recognition of the TV program being watched, the sound of which would be captured by the mobile phone. Several services are dedicated to recognizing the sound recorded by a mobile phone. The most important are Shazam, Soundhound and Mufin. The Shazam service described in US 6,990,453 is the most widespread and works to compare the so-called digital fingerprints made from a sound sample. All available services work to compare fingerprints. Shazam analyzes the sound in which it features distinctive features that will not affect even strong noise and other various signal damage, such as lossy MP3 audio compression or poor recording hardware. Such features are, for example, loud tones. Advanced methods of audio data processing such as cepstral analysis are also used to detect these features. The comparison of these features would be very slow and therefore they are not compared directly, but hash is generated from these features. These hashs are generated from a combination of features (audio frequency η · β they are located) and their distances from each other over time. In this way, many more hashs are generated than the features themselves, thus treating well the situations from damaged signals. The same samples are also used to create a song database to search for samples uploaded by a mobile device. The hash comparison is very fast and therefore can search in a pre-created database with millions of songs. Currently, Shazam also recognizes some selected TV shows.

The Soundhoud described in US Patent Application Publication 2013/0044885 is the second most widely used music recognition service. Like Shazam, they work on digital fingerprints generated from a recorded audio sample. These fingerprints are generated from robust features that do not affect noise and other signal damage. Unlike Shazam, these traits are not generated by hash, but by matrices that capture the relationship between the most distinctive feature and the second and third most distinctive feature in the recorded sample. These matrices are then continuously sent to the server, which compares them to the matrices in the pre-created song sample database. Songs in the database also have more than one matrix that describes them.

Mufin is a service that recognizes live broadcasts on selected TV stations. In addition to recognizing a show and TV station, they can also recognize ads. They use their own AudiolD digital fingerprint and try to find and encode features in the sound that do not affect various damages. Further, US2014 / 0188592 and US2014 / 0012572 disclose adding extra data to a recognized audio, for example, relevant advertising.

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Further known is Blue Spike, which, for example, based on US Patent No. 7,346,472, creates an abstract from a musical sample, which is then compared to an abstract database with the result that it is a song.

This method can be implemented in software generally on digital data, not just on audio.

In the prior art, the Tune Hunter system is known in which samples are recorded from recorded audio from a handheld device (mobile, key chain, pager, etc.), which are then compared to a pre-formed database of music samples. The system will also offer relevant items for sale to the detected sound, such as the song itself. The main difference from the other approaches is in sending and comparing the audio samples themselves and not simplifying them such as hash or matrix as described e.g. in US Patent 6,941,275.

Current song recognition methods work to detect features in audio samples that can survive noise and various signal damage such as lossy MP3 compression, poor recording hardware, and so on. These samples are then encoded into another form (hash, matrix, etc.) that captures the relationships between these features and is easy to compare. In addition to Mufin, most systems compare a sample uploaded by a mobile device to a pre-created database.

Due to the above-mentioned shortcomings in audio recognition, efforts have been made, resulting in the invention further described, which solves a method for reducing the drop in channel viewership during advertising breaks and system engagement.

SUMMARY OF THE INVENTION

The above-mentioned drawbacks are eliminated by a method for reducing the drop in channel viewership during advertising breaks and engagement according to the present invention, which is based on the fact that by activating the control application on a mobile platform server. The broadcast TV signal is

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Sampled in the sampling server and proceeds to the recognition server. The currently selected channel being watched is also brought from the recognition server to the content server. In the other direction of transmission, locked special content for TV advertising is brought to the mobile platform. Opening special TV ad content on the mobile platform is available at the beginning of the advertising break while continuing to watch the same selected channel. Advantageously, at the beginning of the advertising break, a notification of the current moment of the advertisement spot broadcast together with the performance metrics of the spot precedes it. Advantageously, in the second direction of transmission to the mobile platform, aggregated relevant content on social networks is introduced in addition to sending special content to television advertising.

The system connection to reduce the fall in channel viewership during advertising breaks is based on the above method and consists of a sampling server with input from TV broadcasting sources. It also consists of a content server that is wirelessly connected to a mobile platform with a control application. Mobile user platforms are smartphones, laptops, laptops, tablets and similar devices activated in the data network such as mobile Internet or mobile network e.g. GSM. There is a recognition server that is connected to both the sampling server and the content server. The content server comprises at least a first information block with special content for television advertising, and preferably also includes a second information block with aggregated relevant content on social networks that fill the content database. The content server also includes a request server and has input to the external signal generator of the TV broadcasters. The sampling server includes a descriptor generator from the source data. The recognition server includes e.g. index server and comparator with index database.

The functionality of the wiring is as follows. The recognition algorithm is based on input data. From external device - mobile, mobile •

platform is a sample used for recognition, and from the sample server, the data is used as a reference sample to look for a sample from an external device. From both types of equipment, the sample is processed as follows. The raw input data from the data stream is processed by the STFT (Short-time Fourier transform) algorithm. This processing creates a matrix of normalized data energies. Key points are selected from the matrix thus processed using a precisely defined grid. The coordinates of these points together with the processed matrix are input to the BRIEF algorithm, which creates for each key point a set of descriptors that describe the key point and its surroundings. A descriptive set of descriptors from an external device is sent to the content server. A descriptive set of descriptors from the sampling server is sent directly to the recognition server as a reference sample.

The sampling server handles multiple broadcasts from different sources. Each broadcast has a unique identifier (station ID). Each sample of input data from each transmission is independently processed by the algorithm described above and sent with the identifier as a reference descriptive set of descriptors to the recognition server. Increased plausibility of results in an external device is achieved by sending multiple descriptive descriptor sets for recognition and increasing the number of identical recognition responses.

The recognition server receives a descriptive set of descriptors from the content and sampling server. From each received descriptor set received from the sampling server, the extractor selects the exact time interval and creates the extracted descriptor set. According to the identifier, it associates the extracted descriptive set of descriptors with the cluster of previous extracted descriptor sets. At regular intervals, it extracts the extracted descriptor sets from the bursts and joins them into larger descriptor sets representing the overlapping longer time interval for the data stream by identifier. They then join into a time descriptive set of descriptors containing longer time intervals of the descriptive set of descriptors for multiple identifiers. The time sample of the descriptive set of descriptors is an input to the FLANN algorithm that results

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FLANN index stored in the database. The key part is to create different long time samples of descriptive descriptor sets, from which different long FLANN indices are generated. This ensures that the number and length of searches required for sample recognition is minimized. The recognition server maintains a minimum set of differently long FLANN indexes in the database to provide coverage. The incoming descriptive set of descriptors from the content server is sequentially compared in the comparator by the LSH algorithm with only the necessary FLANN indexes from the database to minimize search time. The LSH assigns the key points of the descriptor set from the content server to the closest key points of the descriptive descriptor set currently being compared. Subsequently, the filtering algorithm evaluates the comparison, the score is evaluated and, according to the result, either another search is triggered or the response is sent back to the content server.

A content server is a server containing broadcast information, information about functional recognition servers, and receiving external signals. Its primary role is to provide relevant and up-to-date, complementary information for the content being viewed. The content server maintains a list of currently available recognition servers. After receiving a descriptive set of descriptors from an external source, it selects an available recognition server and sends a descriptive set of descriptors for recognition. If it receives information that the recognition server is busy, it selects another recognition server. It then creates the appropriate content from the recognition server and sends it back to the mobile, mobile platform. This ensures automatic scaling for a large number of recognition requests. The content server is automatically scaled by third-party systems. Another task of the content server is after receiving an external signal (trigger from the TV - signal generator) to change, modify and notify external devices about the change of content.

For the purposes of this invention, the following definitions are set forth:

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The input data is a raw set of data from the source, such as data from an audio stream.

A sampling server is a device capable of processing broadcast / data streams in real time.

A mobile platform is an external device, a mobile, it is a device capable of processing recorded audio.

The normalized energy matrix is an output matrix from the Short-Time Fourier Transform, with the audio input data the x-axis of the overlapping time slots and the y-axis of the frequency intervals.

BRIEF is an algorithm of generating a matrix of normalized energies from input data.

The key point is the coordinates of the selected point from the matrix of normalized energies.

A set of descriptors is a description of a key point and its surroundings in a matrix of normalized energies.

A descriptor descriptor set is a set of descriptor sets for each key point in the normalized energy matrix.

A content server is a device that handles automatic scaling, receives a descriptive set of descriptors from external devices, and sends them for recognition to the recognition server, receiving signals from external sources.

The FLANN index is a structure for fast sample retrieval.

LSH is an algorithm for quickly searching for a descriptive set of descriptors in the FLANN index.

A descriptor descriptor time sample is a descriptor descriptor set from multiple transmissions clustered according to an exact length identifier.

A recognition server is a device that receives a descriptive set of descriptors from the sampling server, aggregates them into a time sample of the descriptive set of descriptors, and creates a database of FLANN indexes. Subsequent to receiving a descriptive set of descriptors from the content server, it compares it only to the necessary set of FLANN indexes and sends the response back.

Advantages of the method for reducing the fall in channel viewership during advertising breaks and system engagement according to this invention are that the system offers viewers the continuation of the viewing experience as a bridging of the advertising break in the form of special content. It will reduce the frustration of interrupting entertainment while reducing the incentive to switch channels. This content is locked during normal broadcast sessions. It unlocks at the beginning of the advertising break and is only available if the viewer does not switch to another station, as the app recognizes the currently selected channel. The mechanism for unlocking special content at the time of each advertising break works by processing the start and end signals. The system also serves as an aggregator of relevant content on social networks. It recognizes individual moments in the broadcast, including advertising. This allows you to bring enhanced TV ad information to your app. The system monitors the broadcast continuously and thus recognizes the broadcasted advertisement and notifies the advertiser of the current moment of broadcasting the advertising spot together with the relevant performance metrics of the spot. The connection to the interface of the visual graphic generator of broadcasters enables direct output of processed data from the system during broadcasting.

BRIEF DESCRIPTION OF THE DRAWINGS

The method for reducing channel overflow in advertising breaks and system engagement according to the invention will be further explained in the drawings, where FIG. 1 shows a schematic diagram of a system connection. In FIG. 2 shows a more detailed system wiring diagram. In FIG. 3 shows a signal sampling scheme.

EXAMPLES

It is to be understood that individual embodiments of the invention are presented for illustration and not as limitations of the technical solutions.

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Those skilled in the art will find or be able to ascertain using no more than routine experimentation many equivalents to specific embodiments of the invention. Such equivalents will also fall within the scope of the following claims. For those skilled in the art, it cannot pose the problem of optimal system design, therefore these features have not been solved in detail.

Example 1

In this example of a particular embodiment of the present invention, a method for reducing the drop in channel viewership during advertising breaks is described. It is based on the fact that by activating the control application on the mobile platform, the audio sample of the currently watched program from the TV scanned by the mobile platform is transferred to the content server in one transmission direction. The broadcast TV signal is sampled in the sampling server and passes to the recognition server. The currently watched selected channel is also brought from the recognition server to the content server. In the second direction of transmission, locked special content for TV advertising and aggregated relevant content on social networks are delivered to the mobile platform in addition to sending special content for TV advertising. Opening special TV ad content on the mobile platform is available at the beginning of the advertising break while continuing to watch the same selected channel. At the beginning of the advertising break, a warning about the current moment of the commercial's commercial, together with the performance metrics of the commercial, precedes it.

Example 2

In this example of a particular embodiment of the invention, a system circuit for reducing the drop in channel viewership during advertising breaks is shown in principle in FIG. 1 and shown in more detail in FIG. 2. It consists of a sampling server 1 with input 2 from distributors 20 of TV broadcasting sources. It consists of a content server 3 which is connected by a wireless two-way link to the mobile platform 4

J · ···· smartphone with control application. Included is a recognition server 5, which is connected to the sampling server 1 and also to the content server 3. The content server 3 comprises a first information block 6 with special content for television advertising and also includes a second information block 7 with aggregated relevant content on the social networks that fill the content database. The content server 3 also comprises a request server 9 and has an input 8 to the external signal generator 14 of the TV broadcasters 15. The content server 3 further comprises a database of TV station metadata 17, a time schedule TV block 19 and a time block 18. The sampling server 1 contains a descriptor generator 10. source data. The recognition server 5 comprises e.g. the indexing server 11 and the comparator 12 with the index database 16. The mobile platform 4 comprises a TV receiver module 21, a descriptor generator 22 of the compared data, a request generator 23, a display module 24 of relevant content and finally a time module 25.

Example 3

In this example of a particular embodiment of the invention, sampling and recognition of input data from data streams as described in FIG. 3. The raw input data from data stream 26 is processed by STFT 36 (Short-time Fourier transform). This processing creates a matrix 27 of normalized data energies. Key points are selected from the matrix 27 thus processed using a predetermined grid. The coordinates of these points, together with the processed matrix, are input to the BRIEF algorithm, a generator 28 that creates, for each keypoint, a set of descriptors that describe the keypoint and its surroundings. A descriptor set 29 from the external mobile platform 4 device is sent to the content server 3. A descriptor set 29 from the sampling server 7 is sent directly to the recognition server 5 as a reference sample. The recognition server 5 receives a descriptive set of descriptors 29 from the content and sampling server 3, LZ of each received descriptive set of descriptors 29 from the sampling server 1, the extractor 30 selects β · · · · · · · «··· ··· exact time interval and create an extracted descriptive set of descriptors

32. Identifies the extracted extracted descriptor set 32 according to the identifier 31 to a cluster of previously extracted descriptor sets 35. At regular intervals, extracts the extracted descriptor sets 35 from the clusters and joins them into larger descriptor sets representing the overlapping longer time interval for the data stream according to These then combine into a time descriptive set of descriptors a sample containing longer descriptive set descriptor time intervals for multiple identifiers. The time sample of the descriptive set of descriptors 33 is an input to the FLANN algorithm, resulting in the FLANN index 34 stored in the database. The key part is to create descriptive sets of descriptor sets of varying length

33, resulting in different long FLANN indices 34. This ensures minimizing the number and length of searches required for sample recognition. The recognition server 5 maintains in the database a minimum set of differently long FLANN indexes 34 to provide coverage. The incoming descriptive set of descriptors from the content server is sequentially compared in the comparator 12 by the LSH algorithm only with the necessary FLANN indexes 34 from the database so as to minimize the search time. LSH assigns the key descriptor descriptors from the content server to the closest key points of the currently descripted descriptor descriptor time sample 33. Subsequently, the filtering algorithm is scored, the score is scored, and either the next search is started or the response is sent back to the content server.

Industrial usability

The method of operating an interactive and efficient electronic advertising system and the system device of the invention find utility in communication technology and advertising.

Claims (8)

PATENT CLAIMS ‘t · 1. A method for reducing channel overflow during advertising breaks, characterized in that in one direction of transmission a sound sample from a TV recorded on a mobile platform recognizes the currently selected channel and in the other direction of transmission a special content locked into the mobile platform. television advertising; opening TV-specific content on the mobile platform is available at the beginning of the advertising break while continuing to watch the same selected channel. A method for reducing the fall in channel viewership during advertising breaks according to claim 1, characterized in that the start of the advertising break is preceded by a notification of the actual moment of broadcast of the advertising spot along with the performance metrics of the spot. Method for reducing the fall in channel viewership during advertising breaks according to claim 1, characterized in that in the second direction of transmission aggregated relevant content on social networks is introduced into the mobile platform. 4. A system connection for reducing the overflow of channels during advertising breaks, characterized in that it consists of a sampling server (1) with an input (2) of TV broadcasting sources, further comprising a content server (3) which is a wireless two-way connection connected to the mobile platform (4) with the control application, wherein there is a recognition server (5) which is connected to the sampling server (1) and also to the content server (3); the content server (3) comprises a first information block (6) with special content for television advertising. •> x * · 4 4 · * A system connection for reducing the overflow of channel viewers during advertising breaks according to claim 4, characterized in that the content server (3) comprises a second information block (7) with aggregated relevant content on social networks. A system connection for reducing the overflow of channel viewers during advertising breaks according to claim 4, characterized in that the content server (3) comprises a request server (9) and has an input (8) for an external signal generator. System connection for reducing the overflow of channels during advertising breaks according to claim 4, characterized in that the sampling server (1) comprises a descriptor generator (10) from the source data. The system circuit for reducing the overflow of channels during advertising breaks according to claim 4, characterized in that the recognition server (5) comprises an index server (11) and a comparator