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Monaural Speech Segregation In Reverberant Environments
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Book Synopsis Monaural Speech Segregation in Reverberant Environments by : Zhaozhang Jin
Download or read book Monaural Speech Segregation in Reverberant Environments written by Zhaozhang Jin and published by . This book was released on 2010 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multipitch tracking in real environments is critical for speech signal processing. Determining pitch in both reverberant and noisy conditions is another difficult task. In the second study, we propose a robust algorithm for multipitch tracking in the presence of background noise and room reverberation. A new channel selection method is utilized to extract periodicity features. We derive pitch scores for each pitch state, which estimate the likelihoods of the observed periodicity features given pitch candidates. An HMM integrates these pitch scores and searches for the best pitch state sequence. Our algorithm can reliably detect single and double pitch contours in noisy and reverberant conditions.
Book Synopsis Auditory-based Algorithms for Sound Segregation in Multisource and Reverberant Environments by : Nicoleta Roman
Download or read book Auditory-based Algorithms for Sound Segregation in Multisource and Reverberant Environments written by Nicoleta Roman and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: At a cocktail party, we can selectively attend to a single voice and filter out other interferences. This perceptual ability has motivated a new field of study known as computational auditory scene analysis (CASA) which aims to build speech separation systems that incorporate auditory principles. The psychological process of figure-ground segregation suggests that the target signal should be segregated as foreground while the remaining stimuli are treated as background. Accordingly, the computational goal of CASA should be to estimate an ideal time-frequency (T-F) binary mask, which selects the target if it is stronger than the interference in a local T-F unit. This dissertation investigates four aspects of CASA processing: location-based speech segregation, binaural tracking of multiple moving sources, binaural sound segregation in reverberation, and monaural segregation of reverberant speech. For localization, the auditory system utilizes the interaural time difference (ITD) and interaural intensity difference (IID) between the ears. We observe that within a narrow frequency band, modifications to the relative strength of the target source with respect to the interference trigger systematic changes for ITD and IID resulting in a characteristic clustering. Consequently, we propose a supervised learning approach to estimate the ideal binary mask. A systematic evaluation shows that the resulting system produces masks very close to the ideal binary ones and large speech intelligibility improvements. In realistic environments, source motion requires consideration. Binaural cues are strongly correlated with locations in T-F units dominated by one source resulting in channel-dependent conditional probabilities. Consequently, we propose a multi-channel integration method of these probabilities in order to compute the likelihood function in a target space. Finally, a hidden Markov model is employed for forming continuous tracks and automatically detecting the number of active sources. Reverberation affects the ITD and IID cues. We therefore propose a binaural segregation system that combines target cancellation through adaptive filtering and a binary decision rule to estimate the ideal binary mask. A major advantage of the proposed system is that it imposes no restrictions on the interfering sources. Quantitative evaluations show that our system outperforms related beamforming approaches. Psychoacoustic evidence suggests that monaural processing play a vital role in segregation. It is known that reverberation smears the harmonicity of speech signals. We therefore propose a two-stage separation system that combines inverse filtering of target room impulse response with pitch-based segregation. As a result of the first stage, the harmonicity of a signal arriving from target direction is partially restored while signals arriving from other locations are further smeared, and this leads to improved segregation and considerable signal-to-noise ratio gains.
Book Synopsis Monaural Speech Segregation by Integrating Primitive and Schema-Based Analysis by :
Download or read book Monaural Speech Segregation by Integrating Primitive and Schema-Based Analysis written by and published by . This book was released on 2008 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: The natural auditory environment typically contains multiple simultaneous events. A remarkable feat of auditory perception is the ability to disentangle the acoustic mixture and group the components of the same event into a stream. This aspect of human audition is called auditory scene analysis (ASA), which has a primitive (bottom-up) process and a schema-based (top-down) process. A major task of auditory scene analysis is monaural segregation of speech from interfering sounds. This project seeks to develop an auditory scene analysis approach to monaural speech segregation. Consistent with the stated objectives of the project, the project has made considerable progress along the following four directions. First, we have proposed a schema-based model for phonemic restoration, which refers to the perceptual synthesis of the phonemes that are masked by appropriate replacement sounds by utilizing lexical context. Second, we have developed an approach to address the problem of sequential organization, which is based on trained speaker models. Third, we have proposed an approach for segmentation of auditory scenes based on event detection, in an attempt to address the segregation of unvoiced speech. Fourth, we have developed a comprehensive system for segregating unvoiced speech, a long standing challenge in computational auditory scene analysis (CASA). In addition, encouraging progress has been made on enhancing reverberant speech and modeling of multitalker speech perception. A provisional patent application entitled "A method for accurate pitch estimation and voice separation," has been filed as a result of this AFOSR grant. Executive summaries of doctoral dissertations supported can be found at the back of the reports.
Book Synopsis Speech Separation by Humans and Machines by : Pierre Divenyi
Download or read book Speech Separation by Humans and Machines written by Pierre Divenyi and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is appropriate for those specializing in speech science, hearing science, neuroscience, or computer science and engineers working on applications such as automatic speech recognition, cochlear implants, hands-free telephones, sound recording, multimedia indexing and retrieval.
Book Synopsis Robust Speech Recognition of Uncertain or Missing Data by : Dorothea Kolossa
Download or read book Robust Speech Recognition of Uncertain or Missing Data written by Dorothea Kolossa and published by Springer Science & Business Media. This book was released on 2011-07-14 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.
Book Synopsis Audio Source Separation and Speech Enhancement by : Emmanuel Vincent
Download or read book Audio Source Separation and Speech Enhancement written by Emmanuel Vincent and published by John Wiley & Sons. This book was released on 2018-07-24 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the technology behind hearing aids, Siri, and Echo Audio source separation and speech enhancement aim to extract one or more source signals of interest from an audio recording involving several sound sources. These technologies are among the most studied in audio signal processing today and bear a critical role in the success of hearing aids, hands-free phones, voice command and other noise-robust audio analysis systems, and music post-production software. Research on this topic has followed three convergent paths, starting with sensor array processing, computational auditory scene analysis, and machine learning based approaches such as independent component analysis, respectively. This book is the first one to provide a comprehensive overview by presenting the common foundations and the differences between these techniques in a unified setting. Key features: Consolidated perspective on audio source separation and speech enhancement. Both historical perspective and latest advances in the field, e.g. deep neural networks. Diverse disciplines: array processing, machine learning, and statistical signal processing. Covers the most important techniques for both single-channel and multichannel processing. This book provides both introductory and advanced material suitable for people with basic knowledge of signal processing and machine learning. Thanks to its comprehensiveness, it will help students select a promising research track, researchers leverage the acquired cross-domain knowledge to design improved techniques, and engineers and developers choose the right technology for their target application scenario. It will also be useful for practitioners from other fields (e.g., acoustics, multimedia, phonetics, and musicology) willing to exploit audio source separation or speech enhancement as pre-processing tools for their own needs.
Book Synopsis Techniques for Noise Robustness in Automatic Speech Recognition by : Tuomas Virtanen
Download or read book Techniques for Noise Robustness in Automatic Speech Recognition written by Tuomas Virtanen and published by John Wiley & Sons. This book was released on 2012-11-28 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech. Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Includes contributions from top ASR researchers from leading research units in the field
Book Synopsis Computational Auditory Scene Analysis by : Deliang Wang
Download or read book Computational Auditory Scene Analysis written by Deliang Wang and published by Wiley-IEEE Press. This book was released on 2006-09-29 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive and coherent account of the state of the art in CASA, in terms of the underlying principles, the algorithms and system architectures that are employed, and the potential applications of this exciting new technology.
Book Synopsis Source Separation and Machine Learning by : Jen-Tzung Chien
Download or read book Source Separation and Machine Learning written by Jen-Tzung Chien and published by Academic Press. This book was released on 2018-10-16 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation. Emphasizes the modern model-based Blind Source Separation (BSS) which closely connects the latest research topics of BSS and Machine Learning Includes coverage of Bayesian learning, sparse learning, online learning, discriminative learning and deep learning Presents a number of case studies of model-based BSS (categorizing them into four modern models - ICA, NMF, NTF and DNN), using a variety of learning algorithms that provide solutions for the construction of BSS systems
Book Synopsis The Journal of the Acoustical Society of America by : Acoustical Society of America
Download or read book The Journal of the Acoustical Society of America written by Acoustical Society of America and published by . This book was released on 2006 with total page 1222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Technology of Binaural Understanding by : Jens Blauert
Download or read book The Technology of Binaural Understanding written by Jens Blauert and published by Springer Nature. This book was released on 2020-08-12 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sound, devoid of meaning, would not matter to us. It is the information sound conveys that helps the brain to understand its environment. Sound and its underlying meaning are always associated with time and space. There is no sound without spatial properties, and the brain always organizes this information within a temporal–spatial framework. This book is devoted to understanding the importance of meaning for spatial and related further aspects of hearing, including cross-modal inference. People, when exposed to acoustic stimuli, do not react directly to what they hear but rather to what they hear means to them. This semiotic maxim may not always apply, for instance, when the reactions are reflexive. But, where it does apply, it poses a major challenge to the builders of models of the auditory system. Take, for example, an auditory model that is meant to be implemented on a robotic agent for autonomous search-&-rescue actions. Or think of a system that can perform judgments on the sound quality of multimedia-reproduction systems. It becomes immediately clear that such a system needs • Cognitive capabilities, including substantial inherent knowledge • The ability to integrate information across different sensory modalities To realize these functions, the auditory system provides a pair of sensory organs, the two ears, and the means to perform adequate preprocessing of the signals provided by the ears. This is realized in the subcortical parts of the auditory system. In the title of a prior book, the term Binaural Listening is used to indicate a focus on sub-cortical functions. Psychoacoustics and auditory signal processing contribute substantially to this area. The preprocessed signals are then forwarded to the cortical parts of the auditory system where, among other things, recognition, classification, localization, scene analysis, assignment of meaning, quality assessment, and action planning take place. Also, information from different sensory modalities is integrated at this level. Between sub-cortical and cortical regions of the auditory system, numerous feedback loops exist that ultimately support the high complexity and plasticity of the auditory system. The current book concentrates on these cognitive functions. Instead of processing signals, processing symbols is now the predominant modeling task. Substantial contributions to the field draw upon the knowledge acquired by cognitive psychology. The keyword Binaural Understanding in the book title characterizes this shift. Both books, The Technology of Binaural Listening and the current one, have been stimulated and supported by AABBA, an open research group devoted to the development and application of models of binaural hearing. The current book is dedicated to technologies that help explain, facilitate, apply, and support various aspects of binaural understanding. It is organized into five parts, each containing three to six chapters in order to provide a comprehensive overview of this emerging area. Each chapter was thoroughly reviewed by at least two anonymous, external experts. The first part deals with the psychophysical and physiological effects of Forming and Interpreting Aural Objects as well as the underlying models. The fundamental concepts of reflexive and reflective auditory feedback are introduced. Mechanisms of binaural attention and attention switching are covered—as well as how auditory Gestalt rules facilitate binaural understanding. A general blackboard architecture is introduced as an example of how machines can learn to form and interpret aural objects to simulate human cognitive listening. The second part, Configuring and Understanding Aural Space, focuses on the human understanding of complex three-dimensional environments—covering the psychological and biological fundamentals of auditory space formation. This part further addresses the human mechanisms used to process information and interact in complex reverberant environments, such as concert halls and forests, and additionally examines how the auditory system can learn to understand and adapt to these environments. The third part is dedicated to Processing Cross-Modal Inference and highlights the fundamental human mechanisms used to integrate auditory cues with cues from other modalities to localize and form perceptual objects. This part also provides a general framework for understanding how complex multimodal scenes can be simulated and rendered. The fourth part, Evaluating Aural-scene Quality and Speech Understanding, focuses on the object-forming aspects of binaural listening and understanding. It addresses cognitive mechanisms involved in both the understanding of speech and the processing of nonverbal information such as Sound Quality and Quality-of- Experience. The aesthetic judgment of rooms is also discussed in this context. Models that simulate underlying human processes and performance are covered in addition to techniques for rendering virtual environments that can then be used to test these models. The fifth part deals with the Application of Cognitive Mechanisms to Audio Technology. It highlights how cognitive mechanisms can be utilized to create spatial auditory illusions using binaural and other 3D-audio technologies. Further, it covers how cognitive binaural technologies can be applied to improve human performance in auditory displays and to develop new auditory technologies for interactive robots. The book concludes with the application of cognitive binaural technologies to the next generation of hearing aids.
Book Synopsis Topics in Acoustic Echo and Noise Control by : Eberhard Hänsler
Download or read book Topics in Acoustic Echo and Noise Control written by Eberhard Hänsler and published by Springer Science & Business Media. This book was released on 2006-08-26 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book treats important topics in "Acoustic Echo and Noise Control" and reports the latest developments. Methods for enhancing the quality of transmitted speech signals are gaining growing attention in universities and in industrial development laboratories. This book, written by an international team of highly qualified experts, concentrates on the modern and advanced methods.
Book Synopsis Hearing - From Sensory Processing to Perception by : B. Kollmeier
Download or read book Hearing - From Sensory Processing to Perception written by B. Kollmeier and published by Springer Science & Business Media. This book was released on 2007-09-19 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hearing – From Sensory Processing to Perception presents the papers of the latest “International Symposium on Hearing”, a meeting held every three years focusing on psychoacoustics and the research of the physiological mechanisms underlying auditory perception. The proceedings provide an up-to-date report on the status of the field of research into hearing and auditory functions. The 59 chapters treat topics such as: the physiological representation of temporal and spectral stimulus properties as a basis for the perception of modulation patterns, pitch and signal intensity; spatial hearing and the physiological mechanisms of binaural processing in mammals; integration of the different stimulus features into auditory scene analysis; physiological mechanisms related to the formation of auditory objects; speech perception; and limitations of auditory perception resulting from hearing disorders.
Book Synopsis Advances in Signal Processing and Intelligent Recognition Systems by : Sabu M. Thampi
Download or read book Advances in Signal Processing and Intelligent Recognition Systems written by Sabu M. Thampi and published by Springer. This book was released on 2017-09-12 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Edited Volume gathers a selection of refereed and revised papers originally presented at the Third International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS’17), held on September 13–16, 2017 in Manipal, India. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. Taken together, they offer a valuable resource for all researchers and scientists engaged in the various fields of signal processing and related areas.
Book Synopsis Blind Source Separation by : Ganesh R. Naik
Download or read book Blind Source Separation written by Ganesh R. Naik and published by Springer. This book was released on 2014-05-21 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms and applications of BSS. Dr. Ganesh R. Naik works at University of Technology, Sydney, Australia; Dr. Wenwu Wang works at University of Surrey, UK.
Book Synopsis Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments by : Xiao-Lei Zhang
Download or read book Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments written by Xiao-Lei Zhang and published by Elsevier. This book was released on 2024-09-04 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition. Provides a comprehensive introduction to the development of deep learning-based robust speech processing Covers speech detection, speech enhancement, dereverberation, multi-speaker speech separation, robust speaker verification, and robust speech recognition Focuses on a historical overview and then covers methods that demonstrate outstanding performance in practical applications
Book Synopsis The Technology of Binaural Listening by : Jens Blauert
Download or read book The Technology of Binaural Listening written by Jens Blauert and published by Springer Science & Business Media. This book was released on 2013-06-07 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the application of advanced models of the human binaural hearing system in modern technology, among others, in the following areas: binaural analysis of aural scenes, binaural de-reverberation, binaural quality assessment of audio channels, loudspeakers and performance spaces, binaural perceptual coding, binaural processing in hearing aids and cochlea implants, binaural systems in robots, binaural/tactile human-machine interfaces, speech-intelligibility prediction in rooms and/or multi-speaker scenarios. An introduction to binaural modeling and an outlook to the future are provided. Further, the book features a MATLAB toolbox to enable readers to construct their own dedicated binaural models on demand.
