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Mental healthcare chatbot based on natural language processing and deep learning approaches: Ted the therapist

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Mental disorder is deliberated to be the top cause of Years Lived with Disability (YLD) with over 29% of the population affected. However, there is a shortage of mental healthcare providers and professionals to manage the huge population. Due to the extremely low number of mental healthcare providers available, one-on-one interaction with all the patients is not possible, which affects their treatment process. This effect severely hinders the treatment process which might result in suicidal behaviour and lead to the death of the patients in some cases. Therefore, there is a need for AI (Artificial Intelligence) techniques that help us to solve this issue. In this paper, we propose an AI web-based chatbot called “Ted” to assist people with mental health-related queries with the help of natural language processing and deep learning approaches. The user message is lemmatized and pre-processed in this step before being passed to the deep-learning model. Then, to specify the question category, an Artificial Neural Network with Softmax is used. This chatbot will allow the users to interact, use natural language to take input, and generate the appropriate response according to the input. The accuracy of our proposed chatbot is 98.13% in providing the appropriate response. In addition to this, “Ted” will help the patients who are reluctant to speak and get stigmatized by the presence of mental healthcare providers.

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Correspondence to Sumit Pandey.

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Pandey, S., Sharma, S. & Wazir, S. Mental healthcare chatbot based on natural language processing and deep learning approaches: Ted the therapist. Int. j. inf. tecnol. 14, 3757–3766 (2022).

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