One example of a hearing device is a hearing-aid device. Modern hearing-aid devices, when employing different hearing programs (typically two to four hearing programs, also termed audiophonic programs), permit their adaptation to varying acoustic environments or scenes. The idea is to optimize the effectiveness of the hearing-aid device for the hearing-aid device user in all situations.
The hearing program can be selected either via a remote control or by means of a selector switch on the hearing-aid device itself. For many users, however, having to switch program settings is a nuisance, or it is difficult, or even impossible. It is also not always easy, even for experienced users of hearing-aid devices, to determine, at what point in time which hearing program is suited best and offers optimum speech intelligibility. An automatic recognition of the acoustic scene and a corresponding automatic switching of the program setting in the hearing-aid device is therefore desirable.
The switch from one hearing program to another can also be considered a change in a transfer function of the hearing device, wherein the transfer function describes signal processing within the hearing system. The transfer function may depend on one or more parameters, also referred to as transfer function parameters, and may then be adjusted by assigning values to said parameters.
There exist several different approaches to the automatic classification of acoustic surroundings. Typically, the methods concerned involve the extraction of different characteristics from an input signal. Based on the so-derived characteristics, a pattern-recognition unit employing a particular algorithm makes a determination as to the attribution of the analyzed signal to a specific acoustic environment.
As examples for classification methods and their application in hearing systems, the following publications shall be named: WO 01/20965 A2, WO 01/22790 A2 and WO 02/32208 A2.
Furthermore, EP 1 670 285 A2, published on Jun. 14, 2006, shall be mentioned, which discloses a training mode for classifiers in hearing devices. It is disclosed that in said training mode, a sound source can be separated by narrow beam-forming. This will isolate the targeted source and, as far as said training mode is on, the classifier will be trained for the targeted source, while other sources of sound are suppressed by said narrow beam-forming. The training provides the classifier with considerable amounts of data on the class represented by the targeted source. This way, an improved reliability of the classification can be achieved.
Not in all situations, hearing program change based on the classification result provides for an optimum hearing sensation for the user. It would be desirable to provide for an improved basis for choosing a hearing program to switch to and/or for the point in time when to switch hearing programs.