A coherent method for finding arrival directions of speech signals and its application for noise reduction in microphone array

The research on finding the arrival directions of speech signals by microphone arrny is proposed. We first analyze the uniform microphone array and give the design for microphone array applied in the hand-free speech recognition. Combining the traditional direction finding technique of MUltiple SIgnal Classification (MUSIC) with the focusing matrix method, we improve the resolving power of the microphone array for multiple speech sources.As one application of finding Direction of Arrival (DOA), a new microphone-array system for noise reduction is proposed. The new system is based on maximum likelihood estimate technique which reconstruct superimposed signals from different directions by using DOA information. The DOA information is got in terms of focusing MUSIC method which has been proven to have high performance than conventional MUSIC method on speaker localization[1].

Application of the direct blast adaptive suppression method to the forward scattered broadband signals

The basic principles of target detection by forward acoustic scattering are presented.A direct blast suppression approach based on adaptive filtering(DBS-AF) is proposed to suppress the direct blast.The DBS-AF technique is extended to the linear frequency modulation(LFM) signal,where the envelope of the signal is regarded as a 'general waveform' and imported into the adaptive filter.Application of the DBS-AF method to the data collected from a lake trial yields an output detection curve,in which the direct blast is mapped to the background while the acoustic field aberration is represented by the peak value fluctuation.The inhibitory effect in single hydrophone is approximately- 5 dB,and is then enhanced by exploiting the mean value removal approach as a preprocessing technique.The direct blast is further suppressed to a level of-10 dB by making full use of multichannel receptions.The main factors affecting the algorithm performance are as follows:the fluctuation degree of the receptions during the weighting vector training period and the power ratio of the forward scattered wave to the direct blast when the target is present.

Discovering API Directives from API Specifications with Text Classification

Application programming interface(API)libraries are extensively used by developers.To correctly program with APIs and avoid bugs,developers shall pay attention to API directives,which illustrate the constraints of APIs.Unfortunately,API directives usually have diverse morphologies,making it time-consuming and error-prone for developers to discover all the relevant API directives.In this paper,we propose an approach leveraging text classification to discover API directives from API specifications.Specifically,given a set of training sentences in API specifications,our approach first characterizes each sentence by three groups of features.Then,to deal with the unequal distribution between API directives and non-directives,our approach employs an under-sampling strategy to split the imbalanced training set into several subsets and trains several classifiers.Given a new sentence in an API specification,our approach synthesizes the trained classifiers to predict whether it is an API directive.We have evaluated our approach over a publicly available annotated API directive corpus.The experimental results reveal that our approach achieves an F-measure value of up to 82.08%.In addition,our approach statistically outperforms the state-of-the-art approach by up to 29.67%in terms of F-measure.