Speech-to-Text and Sentiment Analysis on RTP Streams using AI Cloud Service

Call centers serve as hubs for managing high volumes of telephone inquiries, connecting companies with customers to provide information, assistance, and services. To meet evolving customer demands, call centers are adopting advanced technologies to deliver more efficient and personalized services. Microsoft's Azure Cognitive Services offer a solution leveraging Artificial Intelligence (AI) for seamless speech-to-text conversion and sentiment analysis. With machine learning algorithms and neural networks, Azure Cognitive Services transcribe spoken words into written text and analyze the underlying meaning. The hosting company for the internship recommends leveraging Azure Cognitive Services, aligning with their requirements. Integrating this technology aims to enhance efficiency, effectiveness, and service quality in their call center operations. Speech-to-text plays a pivotal role in this proposed implementation by converting audio streams into textual format. This enables efficient storage of call metadata in databases, improving operational effectiveness. Text-based searches outperform audio searches, enabling quick and accurate access to specific information by call center agents and managers. Sentiment analysis further enhances the implementation by analyzing transcriptions to uncover customer opinions and satisfaction levels. By utilizing natural language processing techniques and sentiment analysis algorithms, call centers gain insights into customer preferences, identify areas for improvement, and tailor services accordingly. Real-time or offline analysis of sentiment analysis results allow for proactive interventions and data-driven decision. The primary objectives are to enhance call metadata storage effectiveness and enable real-time detection of customer satisfaction during service calls. Converting audio streams into text improves call log storage and retrieval efficiency, leading to faster response times and overall operational enhancements. In conclusion, the proposed implementation harnesses Azure Cognitive Services to enhance call center operations, improve database search efficiency, and enable real-time customer satisfaction detection. By leveraging AI-powered techniques, call centers can provide efficient and effective customer service, benefiting both the hosting company and customer experiences.