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Foundation models for natural language processing : pre-trained language models integrating media
Covers basic natural language processing models, pre-trained language models BERT, GPT, and sequence-to-sequence converters, as well as the concepts of self-attention and context-sensitive embedding. Various approaches to improving these models are then discussed, such as expanding the pre-training parameters, increasing the length of input texts, or incorporating additional knowledge. An overview of the best performing models is then provided for about twenty application areas, e.g., question answering, translation, story generation, dialogue systems, image generation from text, etc. For each application area, the strengths and weaknesses of existing models are discussed, and an overview of further developments is provided. In addition, links to freely available code are provided. The concluding chapter summarizes the economic opportunities, risk mitigation, and potential developments of AI.
Designing human interface in speech technology
Designing Human Interface in Speech Technology bridges a gap between the needs of the technical engineer and cognitive researchers working in the multidisciplinary area of speech technology applications. The approach is systematic and the focus is on the utility of developing and designing speech related products. Included is coverage of topics such as neuroscience on the multimodal cortex, cognitive theories on multi-task performance, stress and workload, as well as human information process theory and ecological interface design theory for evaluating speech-related human-system interfaces.
Artificial intelligence for customer relationship management : Solving customer problems
This book describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer.
