Automatic bird species recognition method using their voices is presented in this paper. The selected bird species have been detected by hidden Markov models (HMM) classifier using Mel-frequency cepstral coefficients (MFCC). In order to support recognition process, analysed signals have been appropriately filtered before classification in the so called prefiltration process. The prefiltration strategy assumed using n-th order IIR Butterworth filter bank. Each filter from the filter bank was applied for band pass filtration in the bird species specific and signal type band. Increase of recognition accuracy has been observed in case of prefiltration with properly chosen filter order. Experiments have been carried out on the set of bird voices containing 30 bird species, one of which is endangered with extinction.
The superiority of HFCC features over those of MFCC was demonstrated. Results obtained by DTW methods, mainly by modified phoneme-based DTW classifier, were slightly better in comparison with the HMM classifier. Results obtained for the detection of substitution in pairs (for the correct phonetic charactors please see online article) are very promising. The methods developed for these cases can be integrated into computer systems for speech therapy. For substitutions in pairs (for the correct phonetic charactors please see online article) further research is necessary.
The purpose of this research is to introduce an acoustic camera method to analyze nasality in speech. The input information is generated using an acoustic camera device composed of a 16-channel audio recorder with a microphone array, a high-speed video camera, and Carstens articulograph (model AG500). The linearly constrained minimum variance algorithm is used to provide illustrations of the spatial acoustic field distribution. Acoustic pressure distribution is determined as related to the location of oral, nasal, and oronasal resonances, as well as the root mean square value of the pressure. Durations of particular types of resonances activated in the course of speech sound production are also specified. An example application of the method is discussed for Polish nasalized vowels. The internal structure of the vowels is heterogeneous and involves alternate or simultaneous activation of oral and nasal resonances. The order of appearance of these resonances and their percentage share in the realization of the vowels is determined based on the spatial distribution of the acoustic field. The vowels' structure is demonstrated to be even more complex than suggested in former studies. Furthermore, the proportion of nasality is found to vary significantly between the vowels [ɛw̃] and [ɔw̃].
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