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Bramsløw, Lars; Naithani, Gaurav; Hafez, Atefeh; Barker, Tom; Pontoppidan, Niels Henrik; Virtanen, Tuomas
The Journal of the Acoustical Society of America, 07/2018, Letnik: 144, Številka: 1Journal Article
Hearing aid users are challenged in listening situations with noise and especially speech-on-speech situations with two or more competing voices. Specifically, the task of attending to and segregating two competing voices is particularly hard, unlike for normal-hearing listeners, as shown in a small sub-experiment. In the main experiment, the competing voices benefit of a deep neural network (DNN) based stream segregation enhancement algorithm was tested on hearing-impaired listeners. A mixture of two voices was separated using a DNN and presented to the two ears as individual streams and tested for word score. Compared to the unseparated mixture, there was a 13%-point benefit from the separation, while attending to both voices. If only one output was selected as in a traditional target-masker scenario, a larger benefit of 37%-points was found. The results agreed well with objective metrics and show that for hearing-impaired listeners, DNNs have a large potential for improving stream segregation and speech intelligibility in difficult scenarios with two equally important targets without any prior selection of a primary target stream. An even higher benefit can be obtained if the user can select the preferred target via remote control.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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