Sony Deutschland Gmbh

Sony Corporation

Sony International (Europe) Gmbh

Raquel Tato

Thomas Kemp

Ralf Kompe

Yin Hay Lam

Krzysztof Marasek

Silke Goronzy

Kenta Kawamoto

Masahiro Fujita

Katsuki Minamino

Rika Horinaka

Silke Goronzy-Thomae

Krzystof Marasek

Antoni Abella

The present invention discloses an apparatus for automatic extraction of important events in audio signals comprising:

Apparatus and method for automatic extraction of important events in audio signals

The invention provides a method for processing speech comprising the steps of receiving a speech input (SI) of a speaker, generating speech parameters (SP) from said speech input (SI), determining parameters describing an absolute loudness (L) of said speech input (SI), and evaluating (EV) said speech input (SI) and/or said speech parameters (SP) using said parameters describing the absolute loudness (L). In particular, the step of evaluation (EV) comprises a step of emotion recognition and/or speaker identification. Further, a microphone array comprising a plurality of microphones is used for determining said parameters describing the absolute loudness. With a microphone array the distance of the speaker from the microphone array can be determined and the loudness can be normalized by the distance. Thus, the absolute loudness becomes independent from the distance of the speaker to the microphone, and absolute loudness can now be used as an input parameter for emotion recognition and/or speaker identification.

Method for processing speech using absolute loudness

An apparatus for automatic dissection of segmented audio signals, wherein at least one information signal for identifying programs included in said audio signals and for identifying contents included in said programs. Content detection device detects programs and contents belonging to the respective programs in the information signal. Program weighting device weights each program includes in the information signal based on the contents of the respective program detected by the content detection device. Program ranking device indentifies programmers of the same category and ranking said programs based on a weighting result for each program provided by the program weighting device.

Apparatus and method for automatic dissection of segmented audio signals

To detect and determine a current emotional state (CES) of a human being from a spoken speech input (SI), it is suggested in a method for detecting emotions to identify first and second feature classes (A, E) with, in particular distinct, dimensions of an underlying emotional manifold (EM) or emotional space (ES) and/or with subspaces thereof.

Method for detecting emotions involving subspace specialists

An audio data segmentation apparatus for segmenting of audio data including for supplying audio data, dividing the audio data supplied into audio clips of a predetermined length, discriminating the audio clips into predetermined audio classes, the audio classes identifying a kind of audio data included in the respective audio clip and segmenting for segmenting the audio data into audio meta patterns based on a sequence of audio classes of consecutive audio clips, each meta pattern being allocated to a predetermined type of contents of the audio data. It is difficult to achieve good results with known methods for segmentation of audio data into meta patterns since the rules for the allocation of the meta patterns are dissatisfying. This problem is solved by the inventive audio data segmentation apparatus further including a program database including program data units to identify a certain kind of program, a plurality of respective audio meta patterns being allocated to each program data unit, wherein the segmenting segments the audio data into corresponding audio meta patterns on the basis of the program data units of the program database

Apparatus and method for segmentation of audio data into meta patterns

A method for pre-processing speech, in particular for recognizing speech, including receiving a speech signal, separating a spectrum of said speech signal into a number of predetermined frequency sub-bands, analyzing said speech signal within each of said frequency sub-bands, generating respective band-dependent acoustic feature data for each of said respective frequency sub-bands, deriving band-dependent likelihoods for occurrences of speech elements or within said speech signal based on said band-dependent acoustic feature data, analyzing said speech signal within said spectrum, generating full-band acoustic feature data, which are at least in part representative for said speech signal with respect to said spectrum, deriving a full-band likelihood for occurrences of speech elements or of sequences thereof within said speech signal based on said full-band acoustic feature data, deriving an overall likelihood for occurrences of speech elements within said speech signal based on said band-dependent likelihoods and said full-band likelihood.

Pre-processing speech for speech recognition

To reduce the error rate when classifying emotions from an acoustical speech input (SI) only, it is suggested to include a process of speaker identification to obtain certain speaker identification data (SID) on the basis of which the process of recognizing an emotional state is adapted and/or configured. In particular, speaker-specific feature extractors (FE) and/or emotion classifiers (EC) are selected based on said speaker identification data (SID).

Method for detecting emotions from speech using speaker identification

There is proposed a method that may be universally used for controlling a man-machine interface unit. A learning sample is used in order at least to derive and/or initialize a target action (t) to be carried out and to lead the user from an optional current status (e) to an optional desired target status (e) as the final status (e). This learning sample (l) is formed by a data triple made up by an initial status (e) before an optional action (a) carried out by the user, a final status (e) after the action taken place (a).

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Stuttgart, Germany

Raquel Tato