In recent years, machine learning has been championed as a useful aid for diagnostics. Machine-learning models, for instance, have been developed that can detect words and intonations of speech that may indicate depression.Cognitive approach to learning definition but these models tend to predict that a person is depressed or not, based on the person’s specific answers to specific questions. These methods are accurate, but their reliance on the type of question being asked limits how and where they can be used.Cognitive approach to learning definition

In a paper being presented at the interspeech conference, MIT researchers detail a neural-network model that can be unleashed on raw text and audio data from interviews to discover speech patterns indicative of depression.Cognitive approach to learning definition given a new subject, it can accurately predict if the individual is depressed, without needing any other information about the questions and answers.Cognitive approach to learning definition

The researchers hope this method can be used to develop tools to detect signs of depression in natural conversation. In the future, the model could, for instance, power mobile apps that monitor a user’s text and voice for mental distress and send alerts.Cognitive approach to learning definition this could be especially useful for those who can’t get to a clinician for an initial diagnosis, due to distance, cost, or a lack of awareness that something may be wrong.Cognitive approach to learning definition

“the first hints we have that a person is happy, excited, sad, or has some serious cognitive condition, such as depression, is through their speech,” says first author tuka alhanai, a researcher in the computer science and artificial intelligence laboratory (CSAIL).Cognitive approach to learning definition “if you want to deploy [depression-detection] models in scalable way … you want to minimize the amount of constraints you have on the data you’re using.Cognitive approach to learning definition you want to deploy it in any regular conversation and have the model pick up, from the natural interaction, the state of the individual.”

The technology could still, of course, be used for identifying mental distress in casual conversations in clinical offices, adds co-author james glass, a senior research scientist in CSAIL.Cognitive approach to learning definition “every patient will talk differently, and if the model sees changes maybe it will be a flag to the doctors,” he says. “this is a step forward in seeing if we can do something assistive to help clinicians.”

cognitive approach to learning definition

The key innovation of the model lies in its ability to detect patterns indicative of depression, and then map those patterns to new individuals, with no additional information.Cognitive approach to learning definition “we call it ‘context-free,’ because you’re not putting any constraints into the types of questions you’re looking for and the type of responses to those questions,” alhanai says.Cognitive approach to learning definition

Other models are provided with a specific set of questions, and then given examples of how a person without depression responds and examples of how a person with depression responds — for example, the straightforward inquiry, “do you have a history of depression?” it uses those exact responses to then determine if a new individual is depressed when asked the exact same question.Cognitive approach to learning definition “but that’s not how natural conversations work,” alhanai says.

The researchers, on the other hand, used a technique called sequence modeling, often used for speech processing.Cognitive approach to learning definition with this technique, they fed the model sequences of text and audio data from questions and answers, from both depressed and non-depressed individuals, one by one.Cognitive approach to learning definition as the sequences accumulated, the model extracted speech patterns that emerged for people with or without depression. Words such as, say, “sad,” “low,” or “down,” may be paired with audio signals that are flatter and more monotone.Cognitive approach to learning definition individuals with depression may also speak slower and use longer pauses between words. These text and audio identifiers for mental distress have been explored in previous research.Cognitive approach to learning definition it was ultimately up to the model to determine if any patterns were predictive of depression or not.

The researchers trained and tested their model on a dataset of 142 interactions from the distress analysis interview corpus that contains audio, text, and video interviews of patients with mental-health issues and virtual agents controlled by humans.Cognitive approach to learning definition each subject is rated in terms of depression on a scale between 0 to 27, using the personal health questionnaire. Scores above a cutoff between moderate (10 to 14) and moderately severe (15 to 19) are considered depressed, while all others below that threshold are considered not depressed.Cognitive approach to learning definition out of all the subjects in the dataset, 28 (20 percent) are labeled as depressed.

In experiments, the model was evaluated using metrics of precision and recall.Cognitive approach to learning definition precision measures which of the depressed subjects identified by the model were diagnosed as depressed. Recall measures the accuracy of the model in detecting all subjects who were diagnosed as depressed in the entire dataset.Cognitive approach to learning definition in precision, the model scored 71 percent and, on recall, scored 83 percent. The averaged combined score for those metrics, considering any errors, was 77 percent.Cognitive approach to learning definition in the majority of tests, the researchers’ model outperformed nearly all other models.

One key insight from the research, alhanai notes, is that, during experiments, the model needed much more data to predict depression from audio than text.Cognitive approach to learning definition with text, the model can accurately detect depression using an average of seven question-answer sequences. With audio, the model needed around 30 sequences.Cognitive approach to learning definition “that implies that the patterns in words people use that are predictive of depression happen in shorter time span in text than in audio,” alhanai says.Cognitive approach to learning definition such insights could help the MIT researchers, and others, further refine their models.

This work represents a “very encouraging” pilot, glass says.Cognitive approach to learning definition but now the researchers seek to discover what specific patterns the model identifies across scores of raw data. “right now it’s a bit of a black box,” glass says.Cognitive approach to learning definition “these systems, however, are more believable when you have an explanation of what they’re picking up. … the next challenge is finding out what data it’s seized upon.”