INTELLIGENT PREDICTION OF NEXT STEP SENTENCES FROM A COMMUNICATION SESSION

    公开(公告)号:US20240143936A1

    公开(公告)日:2024-05-02

    申请号:US17978074

    申请日:2022-10-31

    IPC分类号: G06F40/35 G06F40/284

    CPC分类号: G06F40/35 G06F40/284

    摘要: Methods and systems provide for extracting next step sentences from a communication session. In one embodiment, the system defines a set of annotation guidelines for labeling training data; receives a set of labeled training data including sentences from a transcript of a communication session, a subset of the sentences being associated with a positive label; organizes the labeled training data and trains a model with the labeled training data, the training including, for each of the sentences, inputting the sentence into a language model and a classification head to output a number of class probabilities, and inputting a classification token representing the sentence into a classification head; using a number of classifiers from the trained model to generate ensemble class scores; and using the ensemble class scores to predict one or more next step sentences from the sentences in the transcript.

    Predicting Call Volume Using Call Volume Data

    公开(公告)号:US20240267457A1

    公开(公告)日:2024-08-08

    申请号:US18636637

    申请日:2024-04-16

    IPC分类号: H04M3/36 G06N20/00 H04M3/523

    摘要: A machine learning model (e.g., including a deep learning neural network) with learned embeddings is applied to time series data with associated metadata to obtain predictions of the time series value. For example, a call volume in a period of time may be predicted based on call volume data for a sequence of time bins in a window of preceding time. Time bins may be associated with respective metadata, such as day of week, hour of day, day of month, holiday, part of business cycle, weather, and/or tide. These pieces of metadata may be mapped to embedding vectors using trained embedding functions. The resulting embedding vectors may be input to a neural network along with the corresponding time series data (e.g., call volumes) to make a prediction for future time bin. For example, the prediction may be used to provision servers in a network infrastructure.

    Call Volume Prediction
    6.
    发明申请

    公开(公告)号:US20230036270A1

    公开(公告)日:2023-02-02

    申请号:US17390761

    申请日:2021-07-30

    IPC分类号: H04M3/36 H04M3/523 G06N20/00

    摘要: A sequence of call volume measurements is accessed, where each of the call volume measurements is associated with respective metadata. The respective metadata may provide information regarding a time period during which a call volume measurement was made. A window of the sequence of call volume measurements with the respective metadata is input to a machine learning model to obtain a prediction of a call volume. The machine learning model includes embedding functions that are applied to the respective metadata for the call volume measurements in the window.

    Call volume prediction
    8.
    发明授权

    公开(公告)号:US11991308B2

    公开(公告)日:2024-05-21

    申请号:US17390761

    申请日:2021-07-30

    IPC分类号: H04M3/36 G06N20/00 H04M3/523

    摘要: A sequence of call volume measurements is accessed, where each of the call volume measurements is associated with respective metadata. The respective metadata may provide information regarding a time period during which a call volume measurement was made. A window of the sequence of call volume measurements with the respective metadata is input to a machine learning model to obtain a prediction of a call volume. The machine learning model includes embedding functions that are applied to the respective metadata for the call volume measurements in the window.

    INTELLIGENT CONTENT RECOMMENDATION WITHIN A COMMUNICATION SESSION

    公开(公告)号:US20240143678A1

    公开(公告)日:2024-05-02

    申请号:US17978091

    申请日:2022-10-31

    IPC分类号: G06F16/9535 G10L15/08

    摘要: Methods and systems provide for intelligent content recommendation within a communication session. In one embodiment, the system receives a list of content recommendation actions, each content recommendation action being associated with one or more trigger phrases constituting conditions for the content recommendation action to be performed, each trigger phrase being associated with a party the trigger phrase is to be uttered by. The system connects to a communication session with a plurality of participants, and receives a number of utterances associated with the participants in real time. For each utterance, the system determines whether a prediction of relatedness is present between the utterance and one or more trigger phrases associated with a content recommendation action. Upon determining that a prediction of relatedness is present, the system performs the associated content recommendation action by transmitting, to one or more client devices, one or more pieces of content to be recommended.

    DYNAMIC CONVERSATION ALERTS WITHIN A COMMUNICATION SESSION

    公开(公告)号:US20240029727A1

    公开(公告)日:2024-01-25

    申请号:US17871970

    申请日:2022-07-24

    摘要: Methods and systems provide for dynamic conversation alerts within a communication session. In one embodiment, the system presents, to a client device associated with a user of a communication platform, a user interface (“UP”) including a prompt for the user to submit one or more alert phrases, each alert phrase being associated with a category; receives, from the client device, a list of submitted alert phrases; and receives a transcript of a communication session between participants. For each utterance in the transcript, the system determines whether one or more predictions of relatedness are present between the utterance and one or more alert phrases from the list of submitted alert phrases. The system then transmits, to the client device, a list of related categories, each related category including one or more timestamps of utterances for which a prediction of relatedness is present for an alert phrase associated with that category.