1. A computerized method for indicating in real time that an interaction in which a representative of an organization participates is associated with a problem or issue, comprising: capturing the interaction in a storage device by a computing platform comprising a processing apparatus, the interaction comprises at least a speech; receiving a segment of the captured interaction; extracting a feature from the segment wherein the feature is a word spoken in the segment of the interaction obtained by a speech to text mechanism comprising hardware; extracting a global feature associated with the whole interaction in progress; extracting features from segments of the interaction that are earlier to the segment; aggregating the feature and the global feature and features similar to the feature that are related to the segments; classifying the segment of the interaction in association with the problem or issue by applying a model to the feature and the global feature and the features similar to the feature that are related to the segments, wherein extracting the feature from the segment comprises: generating a phoneme graph from the segment of the interaction; flushing a part of the graph by removing graph edges that have no continuity or do not lead to a final state of a HMM, wherein the edges represent candidate phonemes between two time points; coarsely examining the flushed graph and determining a point in the flushed graph of high probability, wherein the point comprises a most probable sub-path of a path; determining a limited time segment window based on the most probable sub-path that covers the sub-paths above or below the most probable sub-path; and performing a thorough search only over the limited time segment window, wherein the thorough search comprises all edges which appear in the limited time window, determining one or more words based on the thorough search, wherein the recited operations are carried out in real time by a computing platform executing one or more computer applications.