Audio objects are associated with positional metadata. A received downmix signal comprises downmix channels that are linear combinations of one or more audio objects and are associated with respective positional locators. In a first aspect, the downmix signal, the positional metadata and frequency-dependent object gains are received. An audio object is reconstructed by applying the object gain to an upmix of the downmix signal in accordance with coefficients based on the positional metadata and the positional locators. In a second aspect, audio objects have been encoded together with at least one bed channel positioned at a positional locator of a corresponding downmix channel. The decoding system receives the downmix signal and the positional metadata of the audio objects. A bed channel is reconstructed by suppressing the content representing audio objects from the corresponding downmix channel on the basis of the positional locator of the corresponding downmix channel.

Audio objects are associated with positional metadata. A received downmix signal comprises downmix channels that are linear combinations of one or more audio objects and are associated with respective positional locators. In a first aspect, the downmix signal, the positional metadata and frequency-dependent object gains are received. An audio object is reconstructed by applying the object gain to an upmix of the downmix signal in accordance with coefficients based on the positional metadata and the positional locators. In a second aspect, audio objects have been encoded together with at least one bed channel positioned at a positional locator of a corresponding downmix channel. The decoding system receives the downmix signal and the positional metadata of the audio objects. A bed channel is reconstructed by suppressing the content representing audio objects from the corresponding downmix channel on the basis of the positional locator of the corresponding downmix channel.

A method is provided that includes obtaining two or more microphone audio signals; analysing the two or more microphone audio signals for a defined noise type; and processing the two or more microphone audio signals based on the analysis to generate at least one audio signal suitable for automatic speech recognition. A corresponding apparatus is also provided.

A method is provided that includes obtaining two or more microphone audio signals; analysing the two or more microphone audio signals for a defined noise type; and processing the two or more microphone audio signals based on the analysis to generate at least one audio signal suitable for automatic speech recognition. A corresponding apparatus is also provided.

To enable accurately determining, based on a sound emitted by an inspection target, a classification of the sound. A control apparatus (1) according to an embodiment includes a classification information acquiring unit (13) that acquires classification information of a sound, a sound acquiring unit (11) that acquires a sound data including information of the sound, a storage unit (20) that stores definition data (25), an extraction unit (12) that extracts a plurality of features of the sound data, and a model construction unit (15) that constructs a learned model where machine learning, based on the plurality of features of the sound data and the classification information, on a correlation between the plurality of features and the classification of the sound is performed.

To enable accurately determining, based on a sound emitted by an inspection target, a classification of the sound. A control apparatus (1) according to an embodiment includes a classification information acquiring unit (13) that acquires classification information of a sound, a sound acquiring unit (11) that acquires a sound data including information of the sound, a storage unit (20) that stores definition data (25), an extraction unit (12) that extracts a plurality of features of the sound data, and a model construction unit (15) that constructs a learned model where machine learning, based on the plurality of features of the sound data and the classification information, on a correlation between the plurality of features and the classification of the sound is performed.

Provided is a system which allows a learner who is a non-native speaker of a given language to intuitively improve pronunciation of the language. A pronunciation conversion apparatus includes a conversion section which converts a first feature value corresponding to a first speech signal obtained when a first speaker who speaks a given language as his/her native language speaks another language such that the first feature value approaches a second feature value corresponding to a second speech signal obtained when a second speaker who speaks the other language as his/her native language speaks the other language, each of the first feature value and the second feature value is a feature value capable of representing a difference in pronunciation, and a speech signal obtained from the first feature value after the conversion is presented to the first speaker.

Provided is a system which allows a learner who is a non-native speaker of a given language to intuitively improve pronunciation of the language. A pronunciation conversion apparatus includes a conversion section which converts a first feature value corresponding to a first speech signal obtained when a first speaker who speaks a given language as his/her native language speaks another language such that the first feature value approaches a second feature value corresponding to a second speech signal obtained when a second speaker who speaks the other language as his/her native language speaks the other language, each of the first feature value and the second feature value is a feature value capable of representing a difference in pronunciation, and a speech signal obtained from the first feature value after the conversion is presented to the first speaker.

An apparatus for estimating an inter-channel time difference between a first channel signal and a second channel signal, includes a signal analyzer for estimating a signal characteristic of the first channel signal or the second channel signal or both signals or a signal derived from the first channel signal or the second channel signal; a calculator for calculating a cross-correlation spectrum for a time block from the first channel signal in the time block and the second channel signal in the time block; a weighter for weighting a smoothed or non-smoothed cross-correlation spectrum to obtain a weighted cross correlation spectrum using a first weighting procedure or using a second weighting procedure depending on a signal characteristic estimated by the signal analyzer, wherein the first weighting procedure is different from the second weighting procedure; and a processor for processing the weighted cross-correlation spectrum to obtain the inter-channel time difference.

An apparatus for estimating an inter-channel time difference between a first channel signal and a second channel signal, includes a signal analyzer for estimating a signal characteristic of the first channel signal or the second channel signal or both signals or a signal derived from the first channel signal or the second channel signal; a calculator for calculating a cross-correlation spectrum for a time block from the first channel signal in the time block and the second channel signal in the time block; a weighter for weighting a smoothed or non-smoothed cross-correlation spectrum to obtain a weighted cross correlation spectrum using a first weighting procedure or using a second weighting procedure depending on a signal characteristic estimated by the signal analyzer, wherein the first weighting procedure is different from the second weighting procedure; and a processor for processing the weighted cross-correlation spectrum to obtain the inter-channel time difference.