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You can probably quickly tell from a friend’s tone of voice whether they’re feeling happy or sad, energetic or exhausted. Computers can already do a similar analysis, and soon they’ll be able to extract a lot more information. It’s something we should all be concerned about, according to Associate Professor in Speech and Language Technology, Tom Bäckström. Personal information encoded in your voice could lead to increased insurance premiums or to advertising that exploits your emotional state. Private information could also be used for harassment, stalking or even extortion. 

‘When someone talks, a lot of information about their health, cultural background, education level and so on is embedded in the speech signal. That information gets transmitted with the speech, even though people don’t realise it,’ says Bäckström, an engineering researcher at Aalto University. For example, even subtle patterns of intonation or word choice can be a giveaway as to your political preferences, while clues in breathing or voice quality may correlate with certain health conditions. 

One important risk is that medical information inferred from voice recordings could affect insurance prices or be used to market medication. Yet Bäckström also highlights the potential for indirect harm. ‘The fear of monitoring or the loss of dignity if people feel like they’re constantly monitored—that’s already psychologically damaging,’ he says. For example, employers might extract personal information from voice recordings which could be used against employees or to screen candidates, or exes might use such tools for stalking or harassment.

‘To ensure privacy, you decide that only a certain amount of information is allowed to leak, and then you build a tool which guarantees that,’ he explains. ‘But with speech, we don’t really know how much information there is. It’s really hard to build tools when you don’t know what you’re protecting, so the first thing is to measure that information.’

The paper offers a metric which can be used to tell how precisely a speaker’s identity can be narrowed down based on the features of a recording, such as the pitch of their speech or its linguistic content. Existing metrics provide measurements in terms of recognition risk, giving an estimate of whether the speaker in a recording can be matched with a specific feature—for example, the likelihood of being able to tell if the speaker has Parkinson’s disease. Bäckström says those approaches are more difficult to understand and generalize. The new metric is the first to capture how much information is contained in an audio clip.

Better science means better tools

Bäckström sees the research as a step towards informing people about the privacy of different speech technologies. ‘I dream of being able to say that, for example, if you give a recording to whatever service, then at a cost of 10 euros, that company will be able to narrow your identity down to, let’s say, a thousand people. That’s something people understand, so it could be reflected in the user interface. Then we can start to discuss things in concrete terms,’ he says.

Having useful metrics isn’t just needed for communicating with the public. It’s also important for designing and evaluating tools to protect privacy. In a paper just published in the Proceedings of IEEE, Bäckström’s team provided the first comprehensive overview of different threats and possible protection strategies, as well as highlighting paths for further research. The paper also covers privacy risks to people who aren’t using speech services, for example, when data from your voice might be captured as background noise in a recording.

The study highlights that preserving privacy isn’t just a technical issue but also a question of the user’s psychology and perceptions, as well as user interface design. 

‘The interface should have ways of communicating how private an interaction is,’ says Bäckström. It should also communicate the system’s competence or confidence to help prevent accidental information leaks or incorrect actions. ‘Communicating those things in the appropriate way helps build long-term trust in a service,’ he adds. 

For Bäckström, addressing privacy concerns doesn’t have to be burdensome but can actually mean improving a product or service. For example, stripping out private information from speech would mean less data is transmitted, bringing down network traffic and reducing costs. 

‘We often see privacy and utility as somehow contradictory forces, but many privacy technologies have utility benefits as well,’ he concludes.

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Link to the paper: