Project description
Training future chatbots
Good customer service is important for any business. The need to answer customer questions and provide them with information without delay can be addressed with chatbots – bots that use artificial intelligence and machine learning to answer basic customer questions. The idea is for customers to interact easily with the business. However, existing language understanding systems are of low quality and make communication unnatural and frustrating for consumers. In this context, the EU-funded BITEXT project proposes a solution based on natural language processing, which trains conversational bots easily and makes their replies more humanlike. The project’s overall goal is to improve the full potential of chatbots so they offer 24/7 service that can be integrated into existing solutions.
Objective
Chatbots are still in their infancy. One of the factors that are currently limiting the development of the chatbots market is the lack of an appealing customer experience. The low quality of the existing natural language understanding systems, negatively impacts user experience.
At BITEXT, we have developed a Natural Language Processing (NLP)-based solution that trains conversational bots easily, and makes their replies more human-alike. Using our Deep Linguistic Analysis Platform (DLAP) and Natural Language Generation (NLG), we improve 3x bot accuracy. This allows existing chatbot frameworks (backend content, chatbot agencies, API integrators and NLP bot engines) to deal with user requests without redesigning their architectures, as we are fully compatible.
BITEXT Innovations, S.L. is a company created in 2007 dedicated to the development and commercialization of resources and linguistic software and technologies of semantic analysis. Among our clients, the Sylicon Valley tech giants, Google, Apple or Amazon. We are a young and fast-growing company, that has opened overseas offices (San Francisco, US), have won innovation prizes and raised Venture Capital (€1M seed funding). But this is only the beginning!
The technological solution of BITEXT is part of the chatbots market which is estimated to be over $4.73 billion in 2024 given that chatbot is the new interface of every frontend or app. The overall goal of the present Phase 2 project is to accelerate bot training and improve human-machine understanding – being the most accurate technology- in this new era of people and machines communication. Also, raise chatbots full-potential, facilitating its development and growth; by being a reliable technology, easy to develop (minimizing manual work) and embeddable into existing solutions and those new to come. Chatbots will assure 24/7 availability, bringing increased response capacity, improving customer support, streamlining inquiries and boosting customer intellige
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences knowledge engineering ontology
- natural sciences computer and information sciences software
- natural sciences computer and information sciences data science natural language processing
- social sciences economics and business business and management commerce e-commerce
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-2 - SME instrument phase 2
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
28232 LAS ROZAS DE MADRID
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.