Estimating the room volume from room impulse response via hypothesis verification approach

In order to understand the acoustic behavior of the sound field in a room, it is important to know the volume of the room, as well as other room parameters, like reverberation time (RT). However, estimating the room volume from the room impulse response (RIR) is usually considered a more difficult task than estimating the RT from the RIR. Most of the existing fully-blind methods for estimating the room volume from the RIR do not have satisfactory performances. The reason is that they are sensitive to differences in source-to-receiver distance and wall reflection coefficients. We propose a new approach in which hypothetical-volume room models are trained, and estimation is performed via hypothesis verification using log-likelihood ratio test (LLRT). We achieve low equal error rate (EER) of 3.6% in hypothesis verification for eight rooms with different values of source-to-receiver distance and wall reflection coefficients.