Methods, systems, and media for automated compliance determination of content items
Abstract
Methods, systems, and media for automated compliance determination of content items are provided. In some embodiments, the method comprises: receiving, at a server from a user device associated with a user, a request to provide a branded content item on a media content platform; in response to receiving the request, generating a transcript of a speech portion of the branded content item; generating a plurality of candidate word sequences based on the transcript; selecting a candidate word sequence from the plurality of candidate word sequences based on a similarity that is determined by comparing each of the plurality of candidate word sequences with each of a plurality of target word sequences; in response to selecting the candidate word sequence, applying a model to the selected candidate word sequence to determine whether the selected candidate word sequence contains a first disclosure statement in accordance with one or more disclosure requirements and applying the model to a content description associated with the branded content item to determine whether the content description contains a second disclosure statement in accordance with the one or more disclosure requirements; and associating the branded content item with a compliance indicator that indicates the branded content item is compliant with the one or more disclosure requirements in response to the model indicating that the selected candidate word sequence contains the first disclosure statement and in response to the model indicating that the content description contains the second disclosure statement.
Claims
exact text as granted — not AI-modified1 . A computer-implemented method for compliance checking content items, the method comprising:
receiving, at a server that includes a hardware processor, from a user device associated with a user, a request to provide a content item on a media content platform; determining, using the hardware processor, a plurality of candidate word sequences having a particular number of words from an audio portion of the content item; selecting, using the hardware processor, a candidate word sequence from the plurality of candidate word sequences based on a similarity that is determined by comparing the plurality of candidate word sequences to each of a plurality of target word sequences; in response to selecting the candidate word sequence, applying, using the hardware processor, a natural language processing model to the selected candidate word sequence to determine whether the selected candidate word sequence contains a first disclosure statement in accordance with one or more disclosure requirements; and causing, using the hardware processor, the content item to be published on the media content platform in response to the natural language processing model indicating that the selected candidate word sequence contains the first disclosure statement.
2 . The computer-implemented method of claim 1 , wherein the content item is identified as being a branded content item.
3 . The computer-implemented method of claim 1 , wherein the method further comprises transcribing an audio portion of a portion of the content item into a transcript of a speech portion of the portion of the content item, wherein the plurality of candidate word sequences are obtained by advancing word-by-word in the transcript.
4 . The computer-implemented method of claim 3 , wherein the method further comprises dividing the transcript of the speech portion of the portion of the content item into the plurality of candidate word sequences having the particular number of words.
5 . The computer-implemented method of claim 3 , wherein the transcript of the speech portion of the portion of the content item is generated by transmitting a content identifier of the content item to a speech-to-text converter that converts speech in the content item to text in the transcript.
6 . The computer-implemented method of claim 1 , wherein the method further comprises associating the content item with a compliance indicator that indicates the content item is compliant with the one or more disclosure requirements, wherein the content item is published on the media content platform based on the compliance indicator indicating that the content item is compliant with the one or more disclosure requirements.
7 . The computer-implemented method of claim 6 , wherein, in response to the natural language processing model indicating that the selected candidate word sequence does not contain the first disclosure statement, the compliance indicator is modified to indicate that the content item is non-compliant with the one or more disclosure requirements.
8 . The computer-implemented method of claim 6 , wherein the method further comprises applying the natural language processing model to a content description associated with the content item to determine whether the content description contains a second disclosure statement in accordance with the one or more disclosure requirements, wherein the content item is published on the media content platform in response to the natural language processing model indicating that the content description contains the first disclosure statement and the second disclosure statement.
9 . The computer-implemented method of claim 8 , wherein, in response to the natural language processing model indicating that the content description does not contain the second disclosure statement, the compliance indicator is modified to indicate that the content item is non-compliant with the one or more disclosure requirements.
10 . The computer-implemented method of claim 6 , wherein, in response to determining that none of the plurality of candidate word sequences has a similarity with one of the plurality of target word sequences greater than the similarity threshold value, the compliance indicator is modified to indicate that the content item is non-compliant with the one or more disclosure requirements.
11 . The computer-implemented method of claim 6 , wherein the compliance indicator is set to indicate that the content item is compliant with the one or more disclosure requirements in response to determining that an output of the natural language processing model is greater than a threshold compliance value.
12 . The computer-implemented method of claim 6 , wherein the method further comprises transmitting the content item and the compliance indicator to a reviewing user prior to providing the content item on the media content platform.
13 . The computer-implemented method of claim 12 , wherein the method further comprises determining whether to transmit the content item and the compliance indicator to the reviewing user based on a risk tolerance associated with the content item.
14 . The computer-implemented method of claim 12 , wherein the method further comprises determining whether to transmit the content item and the compliance indicator to the reviewing user based on a confidence value associated with the compliance indicator.
15 . The computer-implemented method of claim 6 , wherein the method further comprises inhibiting the content item from being published on the media content platform based on the compliance indicator indicating that the content item is non-compliant with the one or more disclosure requirements.
16 . The computer-implemented method of claim 6 , wherein the method further comprises transmitting a notification to the user of the user device that recommends modifications to the content item based on the compliance indicator indicating that the content item is non-compliant with the one or more disclosure requirements.
17 . The computer-implemented method of claim 1 , wherein a time period of the speech portion is selected based on the one or more disclosure requirements requiring that the first disclosure statement is spoken within the time period of the content item.
18 . The computer-implemented method of claim 1 , wherein each of the plurality of candidate word sequences generated from the transcript is a particular length of words.
19 . The computer-implemented method of claim 1 , wherein the similarity is determined by:
generating a plurality of candidate vectors, wherein each of the plurality of candidate word sequences is embedded into a candidate vector; generating a plurality of target vectors, wherein each of the plurality of target word sequences is embedded into a target vector; and comparing each of the plurality of candidate vectors with each of the plurality of target vectors determine a similarity score, wherein the candidate word sequence having a highest similarity score is selected.
20 . The computer-implemented method of claim 19 , wherein the similarity score is determined by calculating cosine similarity between each of the plurality of candidate vectors and each of the plurality of target vectors.
21 . The computer-implemented method of claim 1 , wherein the natural language processing model is applied to a content description associated with the content item to determine whether the content description contains a second disclosure statement in accordance with the one or more disclosure requirements in response to an output of the natural language processing model determining that the selected candidate word sequence is likely to contain the first disclosure statement in accordance with the one or more disclosure requirements.
22 . A system for compliance checking content items, the system comprising:
a hardware processor that:
receives, from a user device associated with a user, a request to provide a content item on a media content platform;
determines a plurality of candidate word sequences having a particular number of words from an audio portion of the content item;
selects a candidate word sequence from the plurality of candidate word sequences based on a similarity that is determined by comparing the plurality of candidate word sequences to each of a plurality of target word sequences;
in response to selecting the candidate word sequence, applies a natural language processing model to the selected candidate word sequence to determine whether the selected candidate word sequence contains a first disclosure statement in accordance with one or more disclosure requirements; and
causes the content item to be published on the media content platform in response to the natural language processing model indicating that the selected candidate word sequence contains the first disclosure statement.
23 . A non-transitory computer-readable medium containing computer executable instructions that, when executed by a processor, cause the processor to perform a method for compliance checking content items, the method comprising:
receiving, at a server, from a user device associated with a user, a request to provide a content item on a media content platform; determining a plurality of candidate word sequences having a particular number of words from an audio portion of the content item; selecting a candidate word sequence from the plurality of candidate word sequences based on a similarity that is determined by comparing the plurality of candidate word sequences to each of a plurality of target word sequences; in response to selecting the candidate word sequence, applying a natural language processing model to the selected candidate word sequence to determine whether the selected candidate word sequence contains a first disclosure statement in accordance with one or more disclosure requirements; and causing the content item to be published on the media content platform in response to the natural language processing model indicating that the selected candidate word sequence contains the first disclosure statement.Join the waitlist — get patent alerts
Track US2023306463A1 — get alerts on status changes and closely related new filings.
We store only your email — no account needed. See our privacy policy.