摘要:
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.
摘要:
An apparatus for classifying audio signals comprises audio signal clipping means for partitioning audio signals into audio clips, and class discrimination means for discriminating the audio clips provided by the audio signal clipping means into predetermined audio classes based on predetermined audio class classifying rules, by analysing acoustic characteristics of the audio signals comprised in the audio clips, wherein a predetermined audio class classifying rule is provided for each audio class, and each audio class represents a respective kind of audio signals comprised in the corresponding audio clip. The determination process to find acceptable audio class classifying rules for each audio class according to the prior art is depending on both the used raw audio signals and the personal experience of the person conducting the determination process. Thus, the determination process usually is very difficult, time consuming and subjective. Furthermore, there is a high risk that not all possible peculiarities of the different programmes and the different categories the audio signal can belong to is sufficiently accounted for. This problem is solved in the inventive apparatus for classifying audio signals by class discrimination means calculating an audio class confidence value for each audio class assigned to an audio clip, wherein the audio class confidence value indicates the likelihood the respective audio class characterises the respective kind of audio signals comprised in the respective audio clip correctly. Furthermore, the class discrimination means use acoustic characteristics of audio clips of audio classes having a high audio class confidence value to train the respective audio class classifying rule.
摘要:
Apparatus and method for automatic dissection of segmented audio signals According to the present invention, an apparatus for automatic dissection of segmented audio signals, wherein at least one information signal for identifying programmes included in said audio signals and for identifying contents included in said programmes is provided, comprises: content detection means for detecting programmes and contents belonging to the respective programmes in the information signal; programme weighting means for weighting each programme comprised in the information signal based on the contents of the respective programme detected by the content detection means; and programme ranking means for identifying programmes of the same category and ranking said programmes based on a weighting result for each programme provided by the programme weighting means.
摘要:
An audio data segmentation apparatus for segmenting of audio data comprises audio data input means for supplying audio data, audio data clipping means for dividing the audio data supplied by the audio data input means into audio clips of a predetermined length, class discrimination means for discriminating the audio clips supplied by the audio data clipping means into predetermined audio classes, the audio classes identifying a kind of audio data included in the respective audio clip and segmenting means 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 comprising a programme database comprising programme data units to identify a certain kind of programme, a plurality of respective audio meta patterns being allocated to each programme data unit, wherein the segmenting means segments the audio data into corresponding audio meta patterns on the basis of the programme data units of the programme database 5.
摘要:
The present invention discloses an apparatus for automatic extraction of important events in audio signals comprising: signal input means for supplying audio signals; audio signal fragmenting means for partitioning audio signals supplied by the signal input means into audio fragments of a predetermined length and for allocating a sequence of one or more audio fragments to a respective audio window; feature extracting means for analyzing acoustic characteristics of the audio signals comprised in the audio fragments and for analyzing acoustic characteristics of the audio signals comprised in the audio windows; and important event extraction means for extracting important events in audio signals supplied by the audio signal fragmenting means based on predetermined important event classifying rules depending on acoustic characteristics of the audio signals comprised in the audio fragments and on acoustic characteristics of the audio signals comprised in the audio windows, wherein each important event extracted by the important event extraction means comprises a discrete sequence of cohesive audio fragments corresponding to an important event included in the audio signals.
摘要:
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 5.
摘要:
The present invention discloses an apparatus for automatic extraction of important events in audio signals comprising: signal input means for supplying audio signals; audio signal fragmenting means for partitioning audio signals supplied by the signal input means into audio fragments of a predetermined length and for allocating a sequence of one or more audio fragments to a respective audio window; feature extracting means for analysing acoustic characteristics of the audio signals comprised in the audio fragments and for analysing acoustic characteristics of the audio signals comprised in the audio windows; and important event extraction means for extracting important events in audio signals supplied by the audio signal fragmenting means based on predetermined important event classifying rules depending on acoustic characteristics of the audio signals comprised in the audio fragments and on acoustic characteristics of the audio signals comprised in the audio windows, wherein each important event extracted by the important event extraction means comprises a discrete sequence of cohesive audio fragments corresponding to an important event included in the audio signals.
摘要:
A method for predicting a misrecognition in a speech recognition system, is based on; the insight that variations in a speech input signal are different depending on the origin of the signal being a speech or a non-speech event. The method comprises steps for receiving a speech input signal, extracting at least one signal variation feature of the speech input signal, and applying a signal variation meter to the speech input signal for deriving a signal variation measure.
摘要:
A method and an apparatus for effecting the method are proposed that allow to define a subset of video signals from a source set of video signals on the basis of meta data available for the source set of video signals. The meta data assign a generic term to a sub-section of the audio channel of the source set of video signals, a class description to one or more sub-units of the sub-section for classifying the origin of the respective sub-unit, a category allocation to a segment, which is formed by a string of one or more classified sub-units of a sub-section, and a rating value to the segment for rating the reliability of the category allocation of the segment. The method includes steps for selecting segments of a sub-section with a rating value above a defined threshold value, assigning a priority value to each category, and specifying a first subset of video signals by defining an arrangement of selected segments by an order based on the respective priority and rating values related to each segment.
摘要:
Based on the insight that variations in a speech input signal are different depending on the origin of the signal being a speech or a non-speech event, the present invention proposes method for predicting a misrecognition in a speech recognition system with steps for receiving a speech input signal, extracting at least one signal variation feature of the speech input signal, and applying a signal variation meter to the speech input signal for deriving a signal variation measure.