siliconindia | | October 20199Microphones trained to listen to and classify different sounds could reshape a number of industrieschines, sometimes wired to the machines and the main-tenance of these systems is not easy, particularly if ma-chines are moved around. Legacy machines may not have any mechanism to collect data. However, sound-based sensors would provide a simple non-touch and non-in-trusive solution to these problems. This would enable industries to use solutions without making many drastic changes to their existing setup.2. Medical DiagnosticsHistorically speaking, audible sound has had two pri-mary uses in healthcare- stethoscopes and medical tran-scription. Stethoscopes are perhaps the most recogniz-able of all medical diagnostic devices used to listen to the heart, lungs, and even blood flow in blood vessels. However, this has always been a non-digital device. With the advent of electronic stethoscopes, sound qual-ity has improved--resulting in better diagnosis--and they can also be recorded and stored for further analysis, consultations with other doctors and more importantly, to train interns, junior doctors and even machine learn-ing models. This presents an opportunity to mine large data sets that can be accumulated over time, and train models that can then diagnose diseases early, and not necessarily with significant human involvement, as is currently required.Medical transcription is also getting a tech over-haul--there are startups which are attempting to tran-scribe voice notes by doctors into text, in real time in-stead of having a team manually to do so.3. Content Creation ToolsWith the increase in the consumption of voice based content, especially podcasts and audiobooks, there is a great demand for voice based content creation and editing tools. With available tools not being very us-er-friendly, there is a lot of scope for innovation in this area, for example, editing audio files using their textual representation.With voice synthesis technology picking up, another use-case can be the creation of audio content with mini-mal effort from the speaker.4. Sound-Based Ads PersonalizationListening to the sound around you gives out a lot of contextual information which can be used to provide a personalized ad experience. An interesting solution for advertisers is by serving relevant ads on your secondary device (for example, your mobile phone), based on the sounds generated by the content you are consuming on your TV or laptop.5. Customer Call AnalysisWith enterprises increasingly investing in keeping their customers happy, it is imperative to analyze their customer interactions in a more detailed and methodi-cal approach instead of on a sampling basis. Howev-er, the amount of customer calls is simply too big for manual analysis.Automating customer call analysis using transcription and then identifying the intent and mood of the customer would go a long way in improving customer happiness. Also, doing it in real time can enable customer support representatives to be guided during the call.There are many challenges in developing solutions which are real time, highly accurate and more important-ly, which ensure `privacy'. But with advances in tech-nology, especially edge-computing, we are bound to see solutions which address all these concerns.
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