Source Extraction in Audio via Background Learning
نویسندگان
چکیده
Source extraction in audio is an important problem in the study of blind source separation (BSS) with many practical applications. It is a challenging problem when the foreground sources to be extracted are weak compared to the background sources. Traditional techniques often do not work in this setting. In this paper we propose a novel technique for extracting foreground sources. This is achieved by an interval of silence for the foreground sources. Using this silence interval one can learn the background information, allowing the removal or suppression of background sources. Very effective optimization schemes are proposed for the case of two sources and two mixtures.
منابع مشابه
Intelligent Single-Channel Methods for Multi-Source Audio Analysis
This thesis investigates the potential of recent machine learning methods for the challenging task of single-channel, multi-source audio audio analysis, i.e., information extraction from single-channel audio where the sources of interest (e.g., speech) are mixed with multiple interfering sources. First, it is shown that source separation by recently proposed techniques for non-negative matrix f...
متن کاملVodcast: A Breakthrough in Developing Incidental Vocabulary Learning
Incidental vocabulary learning is often seen as superior to direct instruction on many occasions. Meanwhile, upon the emergence of the World Wide Web, second language (SL) learners have been introduced to 'podcasts' (recorded audio and video online broadcasts) which could be authentic sources of vocabulary learning. The relatively recent phenomenon of video podcast (vodcast) might be considered...
متن کاملCombining pattern recognition and deep-learning-based algorithms to automatically detect commercial quadcopters using audio signals (Research Article)
Commercial quadcopters with many private, commercial, and public sector applications are a rapidly advancing technology. Currently, there is no guarantee to facilitate the safe operation of these devices in the community. Three different automatic commercial quadcopters identification methods are presented in this paper. Among these three techniques, two are based on deep neural networks in whi...
متن کاملThe Effect of Pre-teaching New Vocabulary Items via Audio-Visuals on Iranian EFL Learners’ Reading Comprehension Ability
This study aimed to investigate the effect of pre-teaching new vocabulary items via audio-visuals on Iranian EFL learners’ reading comprehension ability. The question this study tried to answer is if pre-teaching new vocabulary items via audio-visuals have any effect on Iranian EFL learners’ reading comprehension ability. To find the answer to the question, 30 intermediate level stu...
متن کاملImage alignment via kernelized feature learning
Machine learning is an application of artificial intelligence that is able to automatically learn and improve from experience without being explicitly programmed. The primary assumption for most of the machine learning algorithms is that the training set (source domain) and the test set (target domain) follow from the same probability distribution. However, in most of the real-world application...
متن کامل