Honda Motor Co., Ltd.

Osaka University

Ryu Takeda

Kazuhiro Nakadai

Hiroshi Okuno

Hiroshi Tsujino

Yuji Hasegawa

Kazumasa Murata

Teruhisa Misu

Hirofumi Nakajima

Naoki Hosomi

Kazunori Komatani

Ryusei Taniguchi

A mobile object control device acquires a captured image obtained by capturing an image of surroundings of the mobile object by a camera mounted on a mobile object and an input directive sentence input by a user of the mobile object, inputs, when an image and a directive sentence are input, the captured image and the input directive sentence into a learned model learned to output one or more objects corresponding to the directive sentence in the image together with corresponding degrees of certainty to detect the one or more objects and the corresponding degrees of certainty, sequentially selects the one or more objects based on at least the degree of certainty and makes an inquiry to a user of the mobile object, and causes the mobile object to travel to an indicated position in the input directive sentence, which is specified based on a result of the inquiry.

Mobile object control device, mobile object control method, and storage medium

A spatial normalization unit generates a normalized spectrum by normalizing an orientation component of a microphone array for a target direction included in a spectrum of an acoustic signal acquired from each of a plurality of microphones forming the microphone array into an orientation component for a predetermined standard direction. A mask function estimating unit determines a mask function used for extracting a component of a target sound source arriving in the target direction on the basis of the normalized spectrum using a machine learning model. A mask processing unit estimates the component of the target sound source installed in the target direction by applying the mask function to the acoustic signal.

Acoustic processing device including spatial normalization, mask function estimation, and mask processing, and associated acoustic processing method and storage medium

A reverberation suppressing apparatus, includes: a sound acquiring unit which acquires a sound signal; a reverberation data computing unit which computes reverberation data from the acquired sound signal; a reverberation characteristics estimating unit which estimates reverberation characteristics based on the computed reverberation data; a filter length estimating unit which estimates a filter length of a filter which is used to suppress a reverberation based on the estimated reverberation characteristics; and a reverberation suppressing unit which suppresses the reverberation based on the estimated filter length.

Reverberation suppressing apparatus and reverberation suppressing method

A beat tracking apparatus includes: a filtering unit configured to perform a filtering process on an input acoustic signal and to accentuate an onset; a beat interval reliability calculating unit configured to perform a time-frequency pattern matching process employing a mutual correlation function on the acoustic signal of which the onset is accentuated and to calculate a beat interval reliability; and a beat interval estimating unit configured to estimate a beat interval on the basis of the calculated beat interval reliability.

Beat tracking apparatus, beat tracking method, recording medium, beat tracking program, and robot

A reverberation suppressing apparatus separating sound source signals based on input signals output from microphones collecting the plurality of sound source signals, includes a sound signal output unit generating sound signals and outputting the generated sound signals, a sound acquiring unit acquiring the input signals from microphones, a first evaluation function calculation unit calculating a separation matrix, the input signals, and the sound source signals, and calculating a first evaluation function, a reverberation component suppressing unit calculating an optimal separation matrix, and suppressing a reverberation component by separating the sound source signals other than the generated sound signals, and a separation matrix updating unit dividing a step-size function, approximating each segment to a linear function, calculating step sizes based on the approximated linear functions, and repeatedly updating the separation matrix so that the degree of separation of the sound source signals exceeds the predetermined value.

A robot includes: a sound collecting unit collecting and converting a musical sound into a musical acoustic signal; a voice signal generating unit generating a self-vocalized voice signal; a sound outputting unit converting the self-vocalized voice signal into a sound and outputting the sound; a self-vocalized voice regulating unit receiving the musical acoustic signal and the self-vocalized voice signal; a filtering unit performing a filtering process; a beat interval reliability calculating unit performing a time-frequency pattern matching process and calculating a beat interval reliability; a beat interval estimating unit estimating a beat interval; a beat time reliability calculating unit calculating a beat time reliability; a beat time estimating unit estimating a beat time on the basis of the calculated beat time reliability; a beat time predicting unit predicting a beat time before the current time; and a synchronization unit synchronizing the self-vocalized voice signal.

Robot

A system capable of reducing the influence of sound reverberation or reflection to improve sound-source separation accuracy. An original signal X(&#x3c9;,f) is separated from an observed signal Y(&#x3c9;,f) according to a first model and a second model to extract an unknown signal E(&#x3c9;,f). According to the first model, the original signal X(&#x3c9;,f) of the current frame f is represented as a combined signal of known signals S(&#x3c9;,f&#x2212;m+1) (m=1 to M) that span a certain number M of current and previous frames. This enables extraction of the unknown signal E(&#x3c9;,f) without changing the window length while reducing the influence of reverberation or reflection of the known signal S(&#x3c9;,f) on the observed signal Y(&#x3c9;,f).

Growing community of inventors

Kyoto, Japan

Ryu Takeda