An audio analysis system receives a first recording of a speech signal from an origin audio assembly and a second recording of at least a portion of the speech signal from a receiving audio assembly. The speech signal originates from a speaking user of the origin audio assembly and the second recording is recorded by a receiving audio assembly operated by a different user. Both the origin audio assembly and the receiving audio assembly are located within a room. The audio analysis system selects one or more audio frames in the first recording and one or more audio frames in the second recording that both occur over the same time period. The audio analysis system determines a transfer function for the room based in part on the selected one or more audio frames in the first recording and the selected one or more audio frames in the second recording.

Systems and methods are provided for selecting a preferred type of acoustic insulation apparatus in connection with a particular site. An isolation acoustic measurement corresponding to a reference type of acoustic insulation apparatus and a plurality of difference measurements may be determined. An on-site acoustic measurement corresponding to the reference type of acoustic insulation apparatus may be received. A predicted secondary on-site acoustic measurement may be determined for each distinct secondary type of acoustic insulation apparatus. An on-site ambient noise measurement may be received. The type of acoustic insulation apparatus being associated with the on-site acoustic measurement having the closest value to the on-site ambient noise measurement may be selected as the preferred type of acoustic insulation apparatus in connection with the particular site.

Systems and methods are provided for selecting a preferred type of acoustic insulation apparatus in connection with a particular site. An isolation acoustic measurement corresponding to a reference type of acoustic insulation apparatus and a plurality of difference measurements may be determined. An on-site acoustic measurement corresponding to the reference type of acoustic insulation apparatus may be received. A predicted secondary on-site acoustic measurement may be determined for each distinct secondary type of acoustic insulation apparatus. An on-site ambient noise measurement may be received. The type of acoustic insulation apparatus being associated with the on-site acoustic measurement having the closest value to the on-site ambient noise measurement may be selected as the preferred type of acoustic insulation apparatus in connection with the particular site.

An acoustic characteristic measurement device includes a speaker configured to output an acoustic signal in which a watermark signal is embedded; a microphone configured to perform sound collection with respect to the acoustic signal output from the speaker in a predetermined listening position; and an acoustic characteristic measurement unit configured to determine an acoustic characteristic of an acoustic space from the speaker to the listening position, on the basis of the watermark signal embedded in the acoustic signal which is subjected to the sound collection by the microphone.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for causing a transducer to transmit an acoustic input signal into a member of a device. Receiving a detection signal representing reverberations of the input signal traveling within the member from a receiver. Detecting a contact of the member with an object external to the member based on a change in the detection signal, where the change in the detection signal represents an alteration in the reverberations of the input signal caused by the contact of the member with the object. Determining a position along the member of a point of the contact of the member with the object based on the change in the detection signal.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for causing a transducer to transmit an acoustic input signal into a member of a device. Receiving a detection signal representing reverberations of the input signal traveling within the member from a receiver. Detecting a contact of the member with an object external to the member based on a change in the detection signal, where the change in the detection signal represents an alteration in the reverberations of the input signal caused by the contact of the member with the object. Determining a position along the member of a point of the contact of the member with the object based on the change in the detection signal.

A system and associated method for estimating one or more reverberation parameters includes an adaptive, parametric, linear prediction filter having one or more power spectral density (PSD) estimates of signals of one or more channels as inputs. The prediction filter estimates at least one parameter related to reverberation time, such as T.sub.60, and can further estimate an additional parameter, such as Direct-to-Reverberant Ratio (DRR). The prediction filter may be adapted during a period of reverberation by minimizing a cost function. Adaptation can include using a gradient descent approach, which can operate according to a step size provided by an adaptation controller configured to determine the period of reverberation. One or more microphones can provide the signals. The reverberation parameters estimated can be applied to a reverberation suppressor, with an estimator that does not require a training phase and without relying on assumptions of the user's position relative to the microphones.

A system and associated method for estimating one or more reverberation parameters includes an adaptive, parametric, linear prediction filter having one or more power spectral density (PSD) estimates of signals of one or more channels as inputs. The prediction filter estimates at least one parameter related to reverberation time, such as T.sub.60, and can further estimate an additional parameter, such as Direct-to-Reverberant Ratio (DRR). The prediction filter may be adapted during a period of reverberation by minimizing a cost function. Adaptation can include using a gradient descent approach, which can operate according to a step size provided by an adaptation controller configured to determine the period of reverberation. One or more microphones can provide the signals. The reverberation parameters estimated can be applied to a reverberation suppressor, with an estimator that does not require a training phase and without relying on assumptions of the user's position relative to the microphones.

Example embodiments disclosed herein relate to a estimation of reverberant energy components from audio sources. A method of estimating a reverberant energy component from an active audio source (100) is disclosed. The method comprises determining a correspondence between the active audio source and a plurality of sample sources by comparing one or more spatial features of the active audio source with one or more spatial features of the plurality of sample sources, each of the sample sources being associated with an adaptive filtering model (101); obtaining an adaptive filtering model for the active audio source based on the determined correspondence (102); and estimating the reverberant energy component from the active audio source over time based on the adaptive filtering model (103). Corresponding system (800) and computer program product (900) are also disclosed.

Example embodiments disclosed herein relate to a estimation of reverberant energy components from audio sources. A method of estimating a reverberant energy component from an active audio source (100) is disclosed. The method comprises determining a correspondence between the active audio source and a plurality of sample sources by comparing one or more spatial features of the active audio source with one or more spatial features of the plurality of sample sources, each of the sample sources being associated with an adaptive filtering model (101); obtaining an adaptive filtering model for the active audio source based on the determined correspondence (102); and estimating the reverberant energy component from the active audio source over time based on the adaptive filtering model (103). Corresponding system (800) and computer program product (900) are also disclosed.