The effect of speaker separation and noise level on auditory attention detection

Tine Arras
Auditieve aandachtsdetectie (AAD) analyseert de hersengolven van personen om te bepalen naar wie of wat ze luisteren. In deze scriptie wordt onderzocht welke invloed bepaalde parameters hebben op de accuratesse van AAD. Het bespreekt de resultaten van een experiment met 15 jongvolwassenen met een normaal gehoor.

Je hersenen vertellen naar wie je luistert

Binnenkort lees je misschien deze advertentie in de krant: “Ons nieuwe hoorapparaat is slimmer dan ooit. Het bepaalt automatisch naar wie of wat u luistert en versterkt dit geluid, terwijl het omgevingsgeluiden onderdrukt. Zo hoeft u nooit nog een gesprek te missen en kan u moeiteloos uw partner verstaan in alle omstandigheden, zelfs op restaurant of tijdens een concert. Probeer het nu gratis uit!” Pure sciencefiction? Nee hoor, de technologie bestaat al.

 

Orde in de chaos

Als je verschillende geluiden door elkaar hoort, moeten je hersenen de geluiden van elkaar scheiden. Dat doen ze op basis van bepaalde verschillen en overeenkomsten. Ze letten bijvoorbeeld op de richting waaruit een geluid komt, de luidheid, hoe hoog of laag het geluid is… Zo verdelen ze de geluiden in aparte ‘stromen’, die elk bij één geluidsbron horen. In de volgende stap kan je kiezen naar welke stroom je wil luisteren, afhankelijk van wat je op dat moment het interessantste vindt.

Een voorbeeld: je bent op een receptie. Overal rondom je staan mensen te praten en in combinatie met de achtergrondmuziek is er behoorlijk veel lawaai. Toch kan je, als je je best doet, prima begrijpen wat je gesprekspartner vertelt – of wat iemand anders vertelt, als je een saaie gesprekspartner hebt. Als je erover nadenkt is dat best gek, want met al dat lawaai is het geluid van die ene stem in verhouding niet zo luid. Toch kan het, en wetenschappers hebben er zelfs een naam voor: het cocktail party-effect. Maar hoe werkt dat dan?

Elk geluid dat je hoort wordt door je hersenen verwerkt. Wetenschappers kunnen dat verwerkingsproces afleiden uit je hersengolven; ze noemen het de representatie van geluid. De representatie is gesorteerd per stroom en verandert onder invloed van aandacht. Zodra je besluit om naar een specifieke geluidsbron te luisteren, zal de bijhorende stroom een sterkere representatie krijgen in je hersenen. Tegelijk worden de andere stromen onderdrukt. Zo kan je dus focussen op een bepaald geluid, ook al zijn er nog veel andere geluiden in de omgeving.

 

Science…

Waarom is dat allemaal relevant? Wel, met de juiste apparatuur kunnen onderzoekers je hersengolven meten. Op basis daarvan kunnen ze ontdekken op welk geluid je je aandacht richt. De wetenschappelijke term daarvoor is ‘auditieve aandachtsdetectie’. Het werkt (nog) niet perfect, maar afhankelijk van de situatie heeft de computer het in ongeveer 9 van de 10 gevallen bij het rechte eind. Niet slecht, toch? Voorlopig gebruikt men deze technologie alleen in experimenteel onderzoek, waarbij deelnemers naar twee personen moeten luisteren die door elkaar praten. In mijn masterproef onderzocht ik hoe goed het programma werkt voor een iets complexere situatie: twee vrouwen die door elkaar heen een verhaal vertellen, met een heleboel pratende mensen op de achtergrond. Soms stonden de vrouwen dicht bij elkaar, soms wat verder van elkaar weg. Ook dat bleek de prestatie van het programma te beïnvloeden.

Wetenschappers hopen het programma verder te ontwikkelen om het in hoorapparaten te gebruiken. De belangrijkste klacht van mensen die nu zo’n apparaat dragen, is dat ze het moeilijk hebben om gesprekken te volgen in groep of in lawaai. Dat komt omdat het hoorapparaat alle geluiden versterkt, dus niet alleen wat de gebruiker graag wil horen. Een ‘slim’ hoorapparaat, dat de hersenactiviteit van de gebruiker meet en alleen de gewenste stroom versterkt, kan dat probleem verhelpen.

Jammer genoeg is dat momenteel nog toekomstmuziek. De programma’s zijn alleen getest in eenvoudige situaties, met een beperkt aantal sprekers en met zorgvuldig gekozen geluiden. In het echte leven zijn er natuurlijk geen beperkingen in het aantal en soort geluiden dat er tegelijk hoorbaar is. Bovendien gebruikt men in het onderzoek een badmuts-achtige kap vol elektroden, een schakelkast ter grootte van een schoendoos en een computer om de hersenactiviteit te analyseren. Dat is niet echt handig om mee rond te lopen of mee te nemen op restaurant. Onderzoekers werken wel aan draagbare en minder opvallende alternatieven, maar die staan nog niet op punt. Er moet dus nog veel onderzoek gebeuren voor de technologie bruikbaar is in dagelijkse situaties.

 

…fiction?

Natuurlijk stopt het niet bij hoorapparaten. Een programma dat je hersenactiviteit gebruikt om te ontdekken naar wie of wat je luistert, kan je ook op andere manieren gebruiken. Zo willen zorgverleners een test ontwikkelen die rechtstreeks meet wat je hoort, zonder dat je zelf woorden of zinnen moet nazeggen. Dat is best handig, bijvoorbeeld voor mensen die moeite hebben met praten of die de testinstructies niet begrijpen. Leerkracht willen het programma misschien gebruiken om te ontdekken of hun leerlingen goed opletten in de les. Of de leerlingen dat fijn zullen vinden, is een andere vraag. En het kan nog een stuk extremer. Als je uit hersenactiviteit kan afleiden waaraan iemand aandacht besteedt, kan je dan ook zijn of haar gedachten lezen?

Het is duidelijk dat auditieve aandachtsdetectie een nieuw, maar razend interessant onderwerp is. De technologie biedt mogelijkheden die nuttig zijn voor slechthorenden, maar kan ook op andere manieren ingezet worden. Een ding is zeker: als je over enkele jaren een advertentie leest over slimme hoorapparaten, dan weet je alvast dat mijn masterproef geen sciencefiction was.

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Universiteit of Hogeschool
Logopedische en audiologische wetenschappen
Publicatiejaar
2018
Promotor(en)
Prof. dr. Tom Francart
Kernwoorden