Your smartphone could possibly detect how much you have had to drink by analyzing the way you speak, according to recent scientific findings. It is common knowledge that our voices change significantly after we have consumed a few alcoholic beverages. For instance, anyone who's ever attended a bar's karaoke night can attest to the drastic change in voice modulation after several rounds. Now, research indicates that these vocal alterations can be leveraged to measure the extent of our intoxication.

Scientists have been exploring a variety of self-measuring modalities over the years in a bid to assist individuals in determining when they've crossed their alcohol consumption limits. Several innovative methods have been developed to evaluate our degree of drunkenness and guide us to make better decisions, such as using ride services like Uber, especially when we are too inebriated to drive safely.

A research team from Stanford Medicine and the University of Toronto believes they may have discovered another method of providing instant feedback on an individual's level of intoxication. They conducted a small trial involving 18 adults who were given doses of alcohol according to their body weight. They were then recorded on a smartphone while reading tongue twisters both before and after hourly intervals of drinking. Additionally, the researchers monitored the participants' blood alcohol levels every half an hour over the seven-hour study period.

The researchers then examined the vocal recordings in one-second segments utilizing metrics such as pitch and frequency. After creating a database with this information, it was found that it could predict intoxication levels with an astounding 98% accuracy rate. Brian Suffoletto, the associate professor of emergency medicine at Stanford and lead researcher on the project, expressed his surprise at the model's high degree of accuracy.

According to Suffoletto, adoption of this system into smartphones, allowing access to the device's microphone, could potentially serve as a method to monitor the user's degree of intoxication. Such a system could send alerts when it detects that the user might be too drunk to drive. Suffoletto posits the possibility of such a tool passively collecting data throughout the day, looking for indications of a drinking episode which might necessitate assistance.

This system could be combined with other smartphone features, such as accelerometers to scrutinize unusual walking patterns or an algorithm for analyzing abrupt changes in texting patterns, which could be indicative of great levels of intoxication. Prompt intervention while the individual is still capable of reacting can be facilitated, stated Suffoletto.

Suffoletto further specified that to better understand and validate these findings, more research needs to be conducted. This will ensure a more comprehensive and diverse database of vocal samples is created. The findings from this research have been received positively amongst the scientific community, opening a new direction in the field of alcohol consumption and its detection.