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AI & Analytics

Computer Vision and Audio Analysis

Leverage signal processing and deep learning to capture deeper insights into your image, audio, or video data​.

Simulate human capabilities with deep learning and leverage signal processing techniques to analyze your complex unstructured data sources. Extract derived insights from audio, image, and video data to provide trustworthy enhancements to your business processes and to capture and respond to complex inputs. Our computer vision solutions can help you analyze image and video data, detecting and categorizing important objects as well as identify patterns and anomalies. Improved tracking solutions can be used to detect the location and transition of an object throughout video frames.

Through the use of mathematical and deep learning approaches applied in the context of audio fingerprinting, our team of experts can help you detect and validate your voice information, while various services (cloud proprietary or open-source) can be used to facilitate speech-to-text and text-to-speech applications. Within call centres audio analysis solutions can be used to recognize speaker entities, analyze hold periods, and more comprehensively understand speaker sentiment/intent, allowing you to enhance quality control on your customer support services and deliver superior customer service. Audio analysis techniques can also be used to determine and reduce background and foreground noise, identify music or other unique manufacturing sounds in support of various applications.

Benefits

Unstructured Data Insights
Analyze voice and visual datasets to identify powerful insights to improve business processes, security, and customer satisfaction. Leverage your most complex datasets to assess and validate the impacts of your decisions.

Increased Transparency
Leverage object detection methods to identify any out-of-place objects that should not be present in certain locations. Use tracking and postprocessing techniques to assess if detected objects identify a gap where some other product or item should be located and/or to capture any anomalous behaviors. Dramatically increase coverage and consistency relative to manual surveillance.

Manufacturing Quality Improvements
Identify anomalies or deviations in manufacturing processes and highlight areas for improvement using computer vision applications. Use automatic detection and notification workflows in order to provide operations experts with insightful, real-time information.

Increased Risk Mitigation
Leverage state-of-the-art vision and audio approaches applied to biometrics in order to validate customer identity and to flag mysterious conversations or access attempts. Automatically parse submitted identification cards and historical client conversations to build a signal index. Provide value-added services to customers in the form of video or audio validation.

Applications

Image and Video Segmentation & Identification
Apply visual cognition solutions and deep learning to augment image categorization and detection of specific aspects in images and videos. Identify deviations from common patterns or unwanted content in audio, image, and video files to identify potential problems or anomalous behavior. Moderate user-generated content by filtering out offensive material or monitor manufacturing and business operations to quickly identify and address problems using real-time image analysis.

Logistics Processing & Review
Use image detection approaches to quickly find out-of-place objects and to identify gaps in stock or other space-saving opportunities. Detect and assess speed of response to product gaps and replenishment speeds. Use derived information in order to support optimal distribution center or store layout.

Audio Fingerprinting
Interpret prevalent frequencies in an audio clip to identify powerful insights, identify distinct noises, and map similar audio patterns. Audio analysis can also help in removal of noise from audio samples and in distinguishing background/foreground noise. Using mathematical transformations, your audio files can be converted into a visual representation of speech patterns, and image detection or deep learning architectures can be used to identify patterns and anomalies.

Use Cases

Speech Recognition
Recognize distinct speakers through audio fingerprinting and use intonations and other unique sounds to help identify speaker sentiment. Solutions can be applied in call centers to gauge call urgency and help provide better, timely service. This can also be used to automate QA analysis of calls to determine hold periods and identify opportunities to improve process efficiency.

Image Recognition
Train powerful models to recognize photographs, animated or human drawn images for anomaly detection, social listening and more. Leveraging Convolutional Neural Networks to recognize patterns within images, Adastra's image recognition solutions have the ability to address several use cases. Image classification can help businesses organize vast amounts of visual files and to identify the most relevant parts of documents. Visual cues from image recognition solutions can also be leveraged in marketing to help businesses understand their customers' interests and sentiment toward products or campaigns.

Object Detection and Tracking
Detect objects or people in images and videos and analyze spatial movement in real-time to support the assessment of various traffic applications such as determining client traffic, building occupancy, adherence to social distancing measures, and anomalous movements. Achieve state-of-the-art accuracy in your tracking applications by using estimation theory-based techniques, also offering improvements to speed and efficiency of model design.

Image segmentation
Segment images and extract text/objects from scanned images or documents. Image segmentation solutions can recognize common templates, detect boundaries of a region, and automate the isolation of key pieces of information. OCR approaches can be used to extract relevant text and, when combined with NLP tools, these solutions can be used to recognize pre-trained or custom entities and to tag, classify, or standardize extracted information.

Recognizing Branch Traffic
Detect and identify faces in images and videos to better understand customer or visitor traffic in your branch/office. These solutions can help you determine average service time and identify “missed customers” who leave without availing a service or meeting a representative based on real-time traffic insights thereby offering additional context information for training staff on product and service promotion. 

Image-Based Anomaly Detection
Image-based anomaly detection solutions can be trained to identify deviations from common patterns in manufacturing and send out real-time alerts, for production supervisors to take corrective measures before problems occur. When applied to time-series data, anomaly detection approaches can identify and assessment anomalies over time supporting a wide range of applications in fraud detection, understanding irregularities in business processes, and changes in customer traffic.

Sentiment Analysis
Recognize breathing patterns, voice fluctuations, and pauses in speech and compare them to existing data sources to determine sentiment on customer service calls, voice-based support channels, videos on social media, and other datasets. Get a better understanding of what your customers and audience are saying about your brand in public forums and social media to determine ideal brand responses and marketing tactics.

Methodology

None

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John Yawney

Chief Analytics Officer

John Yawney