Abstract: An audio labeling tool is described for rapidly and efficiently building a labeled data set preferably comprising audio files with annotations denoting speaker transcriptions, speaker identity, periods of silence, background noise, and speaker emotion labels. The tool provides a configurable user interface (UI) with keyboard shortcuts and menu items for streamlined user-guided markup of audio files with context specific labeling and transcription notes. Human audio file labelers will preferably leverage the labeling tool and configurable user interface and menu to rapidly annotate, validate, and build labeled data sets, at scale, of time sliced audio files. The audio labeling tool is preferably applied to audio files and provides an automated means for adding notations, markup, text transcription, and feature labeling to an audio waveform, spectrogram, or other audio data visualization domain for amplifying and highlighting audio feature details.

Abstract: A system and method for providing merchants and service providers automated identification of proximate clients to provide relevant client data and to authorize transactions. Whereupon a client is discreetly identified by the system through facial recognition, thumbprint, voice sample, iris scan, or other biometric sample. Multi-level authorization and authentication are provided using client metadata, such as email, phone number, mobile device, location, and payment information. The service provider is shown client preferences and transaction history in order to facilitate personalized service. The client is provided with relevant options for available goods or services as recommended by the system. The system provides client sentiment analysis to generate dynamic personalization, customer feedback, and intention projection. Service providers and merchants in the network are curated such that they may be presented to a customer in an orderly fashion.